ML_Lab3.ipynb

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  "metadata": {
    "colab": {
      "name": "ML_Lab3",
      "provenance": [],
      "collapsed_sections": [],
      "toc_visible": true,
      "authorship_tag": "ABX9TyOk34Aee7kHTLkdKuVGHVSD",
      "include_colab_link": true
    },
    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
    }
  },
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "view-in-github",
        "colab_type": "text"
      },
      "source": [
        "<a href=\"https://colab.research.google.com/github/JARACH-209/AI-ML_Lab/blob/master/ML_Lab3.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "xFV47NF4Ym0n",
        "colab_type": "text"
      },
      "source": [
        "#ML Lab 3\n",
        "\n",
        "## 1) Simple Linear Regression \n",
        "## Dataset : Swedish Auto Insurance Dataset"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "B3gPKNfvRHQZ",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 162
        },
        "outputId": "e98589a2-6263-424b-cea5-96e1f4b44d36"
      },
      "source": [
        "import pandas as pd\n",
        "import numpy as np\n",
        "from sklearn.linear_model import LinearRegression\n",
        "from sklearn.model_selection import train_test_split\n",
        "from sklearn.linear_model import SGDRegressor\n",
        "from sklearn import preprocessing\n",
        "import matplotlib.pyplot as plt\n",
        "from sklearn.metrics import mean_squared_error\n",
        "from sklearn.metrics import mean_absolute_error\n",
        "import math\n",
        "%matplotlib inline\n",
        "\n",
        "df = pd.read_excel(\"/content/insurance_dataset.xls\")\n",
        "\n",
        "df.head(3)"
      ],
      "execution_count": 165,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "*** No CODEPAGE record, no encoding_override: will use 'ascii'\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>X</th>\n",
              "      <th>Y</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>108</td>\n",
              "      <td>392.5</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>19</td>\n",
              "      <td>46.2</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>13</td>\n",
              "      <td>15.7</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "     X      Y\n",
              "0  108  392.5\n",
              "1   19   46.2\n",
              "2   13   15.7"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 165
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "8N3t13eKcuJO",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 265
        },
        "outputId": "06e10407-5a7c-4bec-a14d-d18921b802d9"
      },
      "source": [
        "fig,ax = plt.subplots()\n",
        "ax.scatter(df.X,df.Y)\n",
        "plt.show()"
      ],
      "execution_count": 166,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "LJECIa5XfLEA",
        "colab_type": "text"
      },
      "source": [
        "Train, Test and Validation Split"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "2efJ55SddPR2",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "#Train and Test set split into 80% and 20% respectively\n",
        "x_train, x_rest, y_train, y_rest = train_test_split(df.X,df.Y,test_size = .4,random_state =0)\n",
        "\n",
        "#Rest of the 40% set split into equal parts of Train and Validation set \n",
        "x_test, x_val, y_test, y_val = train_test_split(x_train,y_train,test_size = .5,random_state = 0)\n",
        "\n",
        "#Therefore : Train = 60%, Test = 20% and Validation = 20%\n"
      ],
      "execution_count": 167,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "LFpW0L_zhWBb",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 73
        },
        "outputId": "c72947eb-13f1-4fec-9386-bb50fbc7b00c"
      },
      "source": [
        "print(len(x_train),len(y_train))\n",
        "print(len(x_val),len(y_val))\n",
        "print(len(x_test),len(y_test))"
      ],
      "execution_count": 168,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "37 37\n",
            "19 19\n",
            "18 18\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "50LRM9i6kTCz",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "x_train = np.array(x_train).reshape(-1,1)\n",
        "y_train = np.array(y_train).reshape(-1,1)\n",
        "x_test = np.array(x_test).reshape(-1,1)\n",
        "y_test = np.array(y_test).reshape(-1,1)\n",
        "x_val = np.array(x_val).reshape(-1,1)\n",
        "y_val = np.array(y_val).reshape(-1,1)"
      ],
      "execution_count": 169,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "_uW25MlZZNn7",
        "colab_type": "text"
      },
      "source": [
        "a) Oridanry Least Squares Method"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "DRs_IXDpd6le",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "clf = LinearRegression(fit_intercept=True,)  #if fit intercept is false then intercept is taken as 0 otherwise it is fit as per the data\n",
        "clf.fit(x_train,y_train)\n",
        "\n",
        "val_score = clf.score(x_val,y_val)\n",
        "test_score = clf.score(x_test,y_test)\n",
        "train_score = clf.score(x_train,y_train)"
      ],
      "execution_count": 170,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "TjW0IRPrg4Zu",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 111
        },
        "outputId": "430c03b1-0cb1-4fe8-a55a-f74eb65b464d"
      },
      "source": [
        "print(\"Validation Score : \",val_score)\n",
        "print(\"Test score : \",test_score)\n",
        "print(\"Train score : \",train_score)\n",
        "print('Coefficients: ', clf.coef_)\n",
        "print('Intercept: ',clf.intercept_)\n",
        "\n",
        "train_y_hat = clf.predict(x_train)\n",
        "test_y_hat = clf.predict(x_test)\n",
        "val_y_hat = clf.predict(x_val)"
      ],
      "execution_count": 171,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Validation Score :  0.9152029466665282\n",
            "Test score :  0.6101251977675606\n",
            "Train score :  0.8707377749067988\n",
            "Coefficients:  [[3.41694874]]\n",
            "Intercept:  [18.31114212]\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "VFOoOs9ql6JO",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 279
        },
        "outputId": "43241b7c-61d8-4762-ff65-efb0cc1eab6b"
      },
      "source": [
        "fig, ax = plt.subplots()\n",
        "ax = plt.scatter(x_train, y_train)\n",
        "ax = plt.plot(x_train, clf.coef_[0][0]*x_train + clf.intercept_[0], '-r')\n",
        "fig = plt.xlabel(\"X\")\n",
        "fig = plt.ylabel(\"Y\")\n",
        "y_hat = clf.predict(x_test)\n",
        "ax = plt.scatter(x_test,y_hat,color = \"green\")\n",
        "plt.show()"
      ],
      "execution_count": 172,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "AnM_fs9Mpt-u",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 167
        },
        "outputId": "b0a916b2-ff66-4f0d-d996-55868f80b3c4"
      },
      "source": [
        "from sklearn.metrics import r2_score\n",
        "\n",
        "print(\"Train R2-score : \\t\\t%.2f\" % r2_score(train_y_hat , y_train) )\n",
        "print(\"Test R2-score : \\t\\t%.2f\" % r2_score(test_y_hat , y_test) )\n",
        "print(\"Validation R2-score : \\t\\t%.2f\" % r2_score(val_y_hat , y_val) )\n",
        "print(\"------------------------------------\")\n",
        "print(\"RMSE test : %.4f\"%math.sqrt(mean_squared_error(y_test,test_y_hat)))\n",
        "print(\"RMSE train : %.4f\"%math.sqrt(mean_squared_error(y_train,train_y_hat)))\n",
        "print(\"MAE test : %.4f\"%mean_absolute_error(y_test,test_y_hat))\n",
        "print(\"MAE train : %.4f\"%mean_absolute_error(y_train,train_y_hat))"
      ],
      "execution_count": 173,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Train R2-score : \t\t0.85\n",
            "Test R2-score : \t\t0.42\n",
            "Validation R2-score : \t\t0.90\n",
            "------------------------------------\n",
            "RMSE test : 35.5350\n",
            "RMSE train : 35.2963\n",
            "MAE test : 30.8211\n",
            "MAE train : 29.7485\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "bzaQN2hFuAnL",
        "colab_type": "text"
      },
      "source": [
        "b) Using Gradient Descent"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "1xgN6uw07JoY",
        "colab_type": "text"
      },
      "source": [
        "**In a SDG regressor it is very important to transform the datasets otherwise output will be nonsensical**"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "QpC1MXxf6jhX",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "scaler = preprocessing.StandardScaler().fit(x_train)\n",
        "x_train = scaler.transform(x_train)\n",
        "x_test = scaler.transform(x_test)\n",
        "x_val = scaler.transform(x_val)\n",
        "\n",
        "y_train = y_train.reshape(-1)\n",
        "y_test = y_test.reshape(-1)\n",
        "y_val = y_val.reshape(-1)"
      ],
      "execution_count": 174,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "ArVv_KTBkRAd",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "def grid_init():\n",
        "    grid = list()\n",
        "    for i in range(-8,1):\n",
        "        grid += [no*(10**i) for no in range(1, 10)]\n",
        "    return grid"
      ],
      "execution_count": 175,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "KZ4Zny-nogw2",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "def grid_search():\n",
        "    best_lrate = None\n",
        "    accuracy = None\n",
        "    best_classifier = None\n",
        "    lrate_acc = {}\n",
        "    best_acc = 1e5 \n",
        "    best_iter = 100\n",
        "\n",
        "    iterations = [100,500,1000,1500,2000,5000,7500,10000,12500,15000,20000,35000,50000,100000,1000000,2500000]\n",
        "    grid = grid_init()\n",
        "    for iter in iterations:\n",
        "        for lrate in grid:\n",
        "            clf = SGDRegressor(max_iter=iter,learning_rate=\"constant\",eta0=lrate)\n",
        "            clf.fit(x_train,y_train)\n",
        "            accuracy = mean_absolute_error(y_test,clf.predict(x_test))\n",
        "            lrate_acc[str(accuracy)] = accuracy\n",
        "\n",
        "            if accuracy < best_acc:\n",
        "                best_acc = accuracy\n",
        "                best_lrate = lrate\n",
        "                best_classifier = clf\n",
        "                best_iter = iter\n",
        "    print(best_acc)\n",
        "    return best_classifier, best_lrate, lrate_acc , iter"
      ],
      "execution_count": 176,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "plgHGBGlrMdi",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1000
        },
        "outputId": "ebb472a2-d28f-4eaa-cb82-1370d78a9127"
      },
      "source": [
        "clf2, lrate, lrate_accuracy, iterations = grid_search()"
      ],
      "execution_count": 177,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "/usr/local/lib/python3.6/dist-packages/sklearn/linear_model/_stochastic_gradient.py:1187: ConvergenceWarning: Maximum number of iteration reached before convergence. Consider increasing max_iter to improve the fit.\n",
            "  ConvergenceWarning)\n",
            "/usr/local/lib/python3.6/dist-packages/sklearn/linear_model/_stochastic_gradient.py:1187: ConvergenceWarning: Maximum number of iteration reached before convergence. Consider increasing max_iter to improve the fit.\n",
            "  ConvergenceWarning)\n",
            "/usr/local/lib/python3.6/dist-packages/sklearn/linear_model/_stochastic_gradient.py:1187: ConvergenceWarning: Maximum number of iteration reached before convergence. Consider increasing max_iter to improve the fit.\n",
            "  ConvergenceWarning)\n",
            "/usr/local/lib/python3.6/dist-packages/sklearn/linear_model/_stochastic_gradient.py:1187: ConvergenceWarning: Maximum number of iteration reached before convergence. Consider increasing max_iter to improve the fit.\n",
            "  ConvergenceWarning)\n",
            "/usr/local/lib/python3.6/dist-packages/sklearn/linear_model/_stochastic_gradient.py:1187: ConvergenceWarning: Maximum number of iteration reached before convergence. Consider increasing max_iter to improve the fit.\n",
            "  ConvergenceWarning)\n",
            "/usr/local/lib/python3.6/dist-packages/sklearn/linear_model/_stochastic_gradient.py:1187: ConvergenceWarning: Maximum number of iteration reached before convergence. Consider increasing max_iter to improve the fit.\n",
            "  ConvergenceWarning)\n",
            "/usr/local/lib/python3.6/dist-packages/sklearn/linear_model/_stochastic_gradient.py:1187: ConvergenceWarning: Maximum number of iteration reached before convergence. Consider increasing max_iter to improve the fit.\n",
            "  ConvergenceWarning)\n",
            "/usr/local/lib/python3.6/dist-packages/sklearn/linear_model/_stochastic_gradient.py:1187: ConvergenceWarning: Maximum number of iteration reached before convergence. Consider increasing max_iter to improve the fit.\n",
            "  ConvergenceWarning)\n",
            "/usr/local/lib/python3.6/dist-packages/sklearn/linear_model/_stochastic_gradient.py:1187: ConvergenceWarning: Maximum number of iteration reached before convergence. Consider increasing max_iter to improve the fit.\n",
            "  ConvergenceWarning)\n",
            "/usr/local/lib/python3.6/dist-packages/sklearn/linear_model/_stochastic_gradient.py:1187: ConvergenceWarning: Maximum number of iteration reached before convergence. Consider increasing max_iter to improve the fit.\n",
            "  ConvergenceWarning)\n",
            "/usr/local/lib/python3.6/dist-packages/sklearn/linear_model/_stochastic_gradient.py:1187: ConvergenceWarning: Maximum number of iteration reached before convergence. Consider increasing max_iter to improve the fit.\n",
            "  ConvergenceWarning)\n",
            "/usr/local/lib/python3.6/dist-packages/sklearn/linear_model/_stochastic_gradient.py:1187: ConvergenceWarning: Maximum number of iteration reached before convergence. Consider increasing max_iter to improve the fit.\n",
            "  ConvergenceWarning)\n",
            "/usr/local/lib/python3.6/dist-packages/sklearn/linear_model/_stochastic_gradient.py:1187: ConvergenceWarning: Maximum number of iteration reached before convergence. Consider increasing max_iter to improve the fit.\n",
            "  ConvergenceWarning)\n",
            "/usr/local/lib/python3.6/dist-packages/sklearn/linear_model/_stochastic_gradient.py:1187: ConvergenceWarning: Maximum number of iteration reached before convergence. Consider increasing max_iter to improve the fit.\n",
            "  ConvergenceWarning)\n",
            "/usr/local/lib/python3.6/dist-packages/sklearn/linear_model/_stochastic_gradient.py:1187: ConvergenceWarning: Maximum number of iteration reached before convergence. Consider increasing max_iter to improve the fit.\n",
            "  ConvergenceWarning)\n",
            "/usr/local/lib/python3.6/dist-packages/sklearn/linear_model/_stochastic_gradient.py:1187: ConvergenceWarning: Maximum number of iteration reached before convergence. Consider increasing max_iter to improve the fit.\n",
            "  ConvergenceWarning)\n",
            "/usr/local/lib/python3.6/dist-packages/sklearn/linear_model/_stochastic_gradient.py:1187: ConvergenceWarning: Maximum number of iteration reached before convergence. Consider increasing max_iter to improve the fit.\n",
            "  ConvergenceWarning)\n",
            "/usr/local/lib/python3.6/dist-packages/sklearn/linear_model/_stochastic_gradient.py:1187: ConvergenceWarning: Maximum number of iteration reached before convergence. Consider increasing max_iter to improve the fit.\n",
            "  ConvergenceWarning)\n",
            "/usr/local/lib/python3.6/dist-packages/sklearn/linear_model/_stochastic_gradient.py:1187: ConvergenceWarning: Maximum number of iteration reached before convergence. Consider increasing max_iter to improve the fit.\n",
            "  ConvergenceWarning)\n",
            "/usr/local/lib/python3.6/dist-packages/sklearn/linear_model/_stochastic_gradient.py:1187: ConvergenceWarning: Maximum number of iteration reached before convergence. Consider increasing max_iter to improve the fit.\n",
            "  ConvergenceWarning)\n",
            "/usr/local/lib/python3.6/dist-packages/sklearn/linear_model/_stochastic_gradient.py:1187: ConvergenceWarning: Maximum number of iteration reached before convergence. Consider increasing max_iter to improve the fit.\n",
            "  ConvergenceWarning)\n",
            "/usr/local/lib/python3.6/dist-packages/sklearn/linear_model/_stochastic_gradient.py:1187: ConvergenceWarning: Maximum number of iteration reached before convergence. Consider increasing max_iter to improve the fit.\n",
            "  ConvergenceWarning)\n",
            "/usr/local/lib/python3.6/dist-packages/sklearn/linear_model/_stochastic_gradient.py:1187: ConvergenceWarning: Maximum number of iteration reached before convergence. Consider increasing max_iter to improve the fit.\n",
            "  ConvergenceWarning)\n",
            "/usr/local/lib/python3.6/dist-packages/sklearn/linear_model/_stochastic_gradient.py:1187: ConvergenceWarning: Maximum number of iteration reached before convergence. Consider increasing max_iter to improve the fit.\n",
            "  ConvergenceWarning)\n",
            "/usr/local/lib/python3.6/dist-packages/sklearn/linear_model/_stochastic_gradient.py:1187: ConvergenceWarning: Maximum number of iteration reached before convergence. Consider increasing max_iter to improve the fit.\n",
            "  ConvergenceWarning)\n",
            "/usr/local/lib/python3.6/dist-packages/sklearn/linear_model/_stochastic_gradient.py:1187: ConvergenceWarning: Maximum number of iteration reached before convergence. Consider increasing max_iter to improve the fit.\n",
            "  ConvergenceWarning)\n",
            "/usr/local/lib/python3.6/dist-packages/sklearn/linear_model/_stochastic_gradient.py:1187: ConvergenceWarning: Maximum number of iteration reached before convergence. Consider increasing max_iter to improve the fit.\n",
            "  ConvergenceWarning)\n",
            "/usr/local/lib/python3.6/dist-packages/sklearn/linear_model/_stochastic_gradient.py:1187: ConvergenceWarning: Maximum number of iteration reached before convergence. Consider increasing max_iter to improve the fit.\n",
            "  ConvergenceWarning)\n",
            "/usr/local/lib/python3.6/dist-packages/sklearn/linear_model/_stochastic_gradient.py:1187: ConvergenceWarning: Maximum number of iteration reached before convergence. Consider increasing max_iter to improve the fit.\n",
            "  ConvergenceWarning)\n",
            "/usr/local/lib/python3.6/dist-packages/sklearn/linear_model/_stochastic_gradient.py:1187: ConvergenceWarning: Maximum number of iteration reached before convergence. Consider increasing max_iter to improve the fit.\n",
            "  ConvergenceWarning)\n",
            "/usr/local/lib/python3.6/dist-packages/sklearn/linear_model/_stochastic_gradient.py:1187: ConvergenceWarning: Maximum number of iteration reached before convergence. Consider increasing max_iter to improve the fit.\n",
            "  ConvergenceWarning)\n",
            "/usr/local/lib/python3.6/dist-packages/sklearn/linear_model/_stochastic_gradient.py:1187: ConvergenceWarning: Maximum number of iteration reached before convergence. Consider increasing max_iter to improve the fit.\n",
            "  ConvergenceWarning)\n",
            "/usr/local/lib/python3.6/dist-packages/sklearn/linear_model/_stochastic_gradient.py:1187: ConvergenceWarning: Maximum number of iteration reached before convergence. Consider increasing max_iter to improve the fit.\n",
            "  ConvergenceWarning)\n",
            "/usr/local/lib/python3.6/dist-packages/sklearn/linear_model/_stochastic_gradient.py:1187: ConvergenceWarning: Maximum number of iteration reached before convergence. Consider increasing max_iter to improve the fit.\n",
            "  ConvergenceWarning)\n",
            "/usr/local/lib/python3.6/dist-packages/sklearn/linear_model/_stochastic_gradient.py:1187: ConvergenceWarning: Maximum number of iteration reached before convergence. Consider increasing max_iter to improve the fit.\n",
            "  ConvergenceWarning)\n",
            "/usr/local/lib/python3.6/dist-packages/sklearn/linear_model/_stochastic_gradient.py:1187: ConvergenceWarning: Maximum number of iteration reached before convergence. Consider increasing max_iter to improve the fit.\n",
            "  ConvergenceWarning)\n",
            "/usr/local/lib/python3.6/dist-packages/sklearn/linear_model/_stochastic_gradient.py:1187: ConvergenceWarning: Maximum number of iteration reached before convergence. Consider increasing max_iter to improve the fit.\n",
            "  ConvergenceWarning)\n",
            "/usr/local/lib/python3.6/dist-packages/sklearn/linear_model/_stochastic_gradient.py:1187: ConvergenceWarning: Maximum number of iteration reached before convergence. Consider increasing max_iter to improve the fit.\n",
            "  ConvergenceWarning)\n",
            "/usr/local/lib/python3.6/dist-packages/sklearn/linear_model/_stochastic_gradient.py:1187: ConvergenceWarning: Maximum number of iteration reached before convergence. Consider increasing max_iter to improve the fit.\n",
            "  ConvergenceWarning)\n",
            "/usr/local/lib/python3.6/dist-packages/sklearn/linear_model/_stochastic_gradient.py:1187: ConvergenceWarning: Maximum number of iteration reached before convergence. Consider increasing max_iter to improve the fit.\n",
            "  ConvergenceWarning)\n",
            "/usr/local/lib/python3.6/dist-packages/sklearn/linear_model/_stochastic_gradient.py:1187: ConvergenceWarning: Maximum number of iteration reached before convergence. Consider increasing max_iter to improve the fit.\n",
            "  ConvergenceWarning)\n",
            "/usr/local/lib/python3.6/dist-packages/sklearn/linear_model/_stochastic_gradient.py:1187: ConvergenceWarning: Maximum number of iteration reached before convergence. Consider increasing max_iter to improve the fit.\n",
            "  ConvergenceWarning)\n",
            "/usr/local/lib/python3.6/dist-packages/sklearn/linear_model/_stochastic_gradient.py:1187: ConvergenceWarning: Maximum number of iteration reached before convergence. Consider increasing max_iter to improve the fit.\n",
            "  ConvergenceWarning)\n",
            "/usr/local/lib/python3.6/dist-packages/sklearn/linear_model/_stochastic_gradient.py:1187: ConvergenceWarning: Maximum number of iteration reached before convergence. Consider increasing max_iter to improve the fit.\n",
            "  ConvergenceWarning)\n",
            "/usr/local/lib/python3.6/dist-packages/sklearn/linear_model/_stochastic_gradient.py:1187: ConvergenceWarning: Maximum number of iteration reached before convergence. Consider increasing max_iter to improve the fit.\n",
            "  ConvergenceWarning)\n",
            "/usr/local/lib/python3.6/dist-packages/sklearn/linear_model/_stochastic_gradient.py:1187: ConvergenceWarning: Maximum number of iteration reached before convergence. Consider increasing max_iter to improve the fit.\n",
            "  ConvergenceWarning)\n",
            "/usr/local/lib/python3.6/dist-packages/sklearn/linear_model/_stochastic_gradient.py:1187: ConvergenceWarning: Maximum number of iteration reached before convergence. Consider increasing max_iter to improve the fit.\n",
            "  ConvergenceWarning)\n",
            "/usr/local/lib/python3.6/dist-packages/sklearn/linear_model/_stochastic_gradient.py:1187: ConvergenceWarning: Maximum number of iteration reached before convergence. Consider increasing max_iter to improve the fit.\n",
            "  ConvergenceWarning)\n",
            "/usr/local/lib/python3.6/dist-packages/sklearn/linear_model/_stochastic_gradient.py:1187: ConvergenceWarning: Maximum number of iteration reached before convergence. Consider increasing max_iter to improve the fit.\n",
            "  ConvergenceWarning)\n",
            "/usr/local/lib/python3.6/dist-packages/sklearn/linear_model/_stochastic_gradient.py:1187: ConvergenceWarning: Maximum number of iteration reached before convergence. Consider increasing max_iter to improve the fit.\n",
            "  ConvergenceWarning)\n",
            "/usr/local/lib/python3.6/dist-packages/sklearn/linear_model/_stochastic_gradient.py:1187: ConvergenceWarning: Maximum number of iteration reached before convergence. Consider increasing max_iter to improve the fit.\n",
            "  ConvergenceWarning)\n",
            "/usr/local/lib/python3.6/dist-packages/sklearn/linear_model/_stochastic_gradient.py:1187: ConvergenceWarning: Maximum number of iteration reached before convergence. Consider increasing max_iter to improve the fit.\n",
            "  ConvergenceWarning)\n",
            "/usr/local/lib/python3.6/dist-packages/sklearn/linear_model/_stochastic_gradient.py:1187: ConvergenceWarning: Maximum number of iteration reached before convergence. Consider increasing max_iter to improve the fit.\n",
            "  ConvergenceWarning)\n",
            "/usr/local/lib/python3.6/dist-packages/sklearn/linear_model/_stochastic_gradient.py:1187: ConvergenceWarning: Maximum number of iteration reached before convergence. Consider increasing max_iter to improve the fit.\n",
            "  ConvergenceWarning)\n",
            "/usr/local/lib/python3.6/dist-packages/sklearn/linear_model/_stochastic_gradient.py:1187: ConvergenceWarning: Maximum number of iteration reached before convergence. Consider increasing max_iter to improve the fit.\n",
            "  ConvergenceWarning)\n",
            "/usr/local/lib/python3.6/dist-packages/sklearn/linear_model/_stochastic_gradient.py:1187: ConvergenceWarning: Maximum number of iteration reached before convergence. Consider increasing max_iter to improve the fit.\n",
            "  ConvergenceWarning)\n",
            "/usr/local/lib/python3.6/dist-packages/sklearn/linear_model/_stochastic_gradient.py:1187: ConvergenceWarning: Maximum number of iteration reached before convergence. Consider increasing max_iter to improve the fit.\n",
            "  ConvergenceWarning)\n",
            "/usr/local/lib/python3.6/dist-packages/sklearn/linear_model/_stochastic_gradient.py:1187: ConvergenceWarning: Maximum number of iteration reached before convergence. Consider increasing max_iter to improve the fit.\n",
            "  ConvergenceWarning)\n",
            "/usr/local/lib/python3.6/dist-packages/sklearn/linear_model/_stochastic_gradient.py:1187: ConvergenceWarning: Maximum number of iteration reached before convergence. Consider increasing max_iter to improve the fit.\n",
            "  ConvergenceWarning)\n",
            "/usr/local/lib/python3.6/dist-packages/sklearn/linear_model/_stochastic_gradient.py:1187: ConvergenceWarning: Maximum number of iteration reached before convergence. Consider increasing max_iter to improve the fit.\n",
            "  ConvergenceWarning)\n",
            "/usr/local/lib/python3.6/dist-packages/sklearn/linear_model/_stochastic_gradient.py:1187: ConvergenceWarning: Maximum number of iteration reached before convergence. Consider increasing max_iter to improve the fit.\n",
            "  ConvergenceWarning)\n",
            "/usr/local/lib/python3.6/dist-packages/sklearn/linear_model/_stochastic_gradient.py:1187: ConvergenceWarning: Maximum number of iteration reached before convergence. Consider increasing max_iter to improve the fit.\n",
            "  ConvergenceWarning)\n",
            "/usr/local/lib/python3.6/dist-packages/sklearn/linear_model/_stochastic_gradient.py:1187: ConvergenceWarning: Maximum number of iteration reached before convergence. Consider increasing max_iter to improve the fit.\n",
            "  ConvergenceWarning)\n",
            "/usr/local/lib/python3.6/dist-packages/sklearn/linear_model/_stochastic_gradient.py:1187: ConvergenceWarning: Maximum number of iteration reached before convergence. Consider increasing max_iter to improve the fit.\n",
            "  ConvergenceWarning)\n",
            "/usr/local/lib/python3.6/dist-packages/sklearn/linear_model/_stochastic_gradient.py:1187: ConvergenceWarning: Maximum number of iteration reached before convergence. Consider increasing max_iter to improve the fit.\n",
            "  ConvergenceWarning)\n",
            "/usr/local/lib/python3.6/dist-packages/sklearn/linear_model/_stochastic_gradient.py:1187: ConvergenceWarning: Maximum number of iteration reached before convergence. Consider increasing max_iter to improve the fit.\n",
            "  ConvergenceWarning)\n",
            "/usr/local/lib/python3.6/dist-packages/sklearn/linear_model/_stochastic_gradient.py:1187: ConvergenceWarning: Maximum number of iteration reached before convergence. Consider increasing max_iter to improve the fit.\n",
            "  ConvergenceWarning)\n",
            "/usr/local/lib/python3.6/dist-packages/sklearn/linear_model/_stochastic_gradient.py:1187: ConvergenceWarning: Maximum number of iteration reached before convergence. Consider increasing max_iter to improve the fit.\n",
            "  ConvergenceWarning)\n",
            "/usr/local/lib/python3.6/dist-packages/sklearn/linear_model/_stochastic_gradient.py:1187: ConvergenceWarning: Maximum number of iteration reached before convergence. Consider increasing max_iter to improve the fit.\n",
            "  ConvergenceWarning)\n",
            "/usr/local/lib/python3.6/dist-packages/sklearn/linear_model/_stochastic_gradient.py:1187: ConvergenceWarning: Maximum number of iteration reached before convergence. Consider increasing max_iter to improve the fit.\n",
            "  ConvergenceWarning)\n",
            "/usr/local/lib/python3.6/dist-packages/sklearn/linear_model/_stochastic_gradient.py:1187: ConvergenceWarning: Maximum number of iteration reached before convergence. Consider increasing max_iter to improve the fit.\n",
            "  ConvergenceWarning)\n",
            "/usr/local/lib/python3.6/dist-packages/sklearn/linear_model/_stochastic_gradient.py:1187: ConvergenceWarning: Maximum number of iteration reached before convergence. Consider increasing max_iter to improve the fit.\n",
            "  ConvergenceWarning)\n",
            "/usr/local/lib/python3.6/dist-packages/sklearn/linear_model/_stochastic_gradient.py:1187: ConvergenceWarning: Maximum number of iteration reached before convergence. Consider increasing max_iter to improve the fit.\n",
            "  ConvergenceWarning)\n",
            "/usr/local/lib/python3.6/dist-packages/sklearn/linear_model/_stochastic_gradient.py:1187: ConvergenceWarning: Maximum number of iteration reached before convergence. Consider increasing max_iter to improve the fit.\n",
            "  ConvergenceWarning)\n",
            "/usr/local/lib/python3.6/dist-packages/sklearn/linear_model/_stochastic_gradient.py:1187: ConvergenceWarning: Maximum number of iteration reached before convergence. Consider increasing max_iter to improve the fit.\n",
            "  ConvergenceWarning)\n",
            "/usr/local/lib/python3.6/dist-packages/sklearn/linear_model/_stochastic_gradient.py:1187: ConvergenceWarning: Maximum number of iteration reached before convergence. Consider increasing max_iter to improve the fit.\n",
            "  ConvergenceWarning)\n",
            "/usr/local/lib/python3.6/dist-packages/sklearn/linear_model/_stochastic_gradient.py:1187: ConvergenceWarning: Maximum number of iteration reached before convergence. Consider increasing max_iter to improve the fit.\n",
            "  ConvergenceWarning)\n",
            "/usr/local/lib/python3.6/dist-packages/sklearn/linear_model/_stochastic_gradient.py:1187: ConvergenceWarning: Maximum number of iteration reached before convergence. Consider increasing max_iter to improve the fit.\n",
            "  ConvergenceWarning)\n",
            "/usr/local/lib/python3.6/dist-packages/sklearn/linear_model/_stochastic_gradient.py:1187: ConvergenceWarning: Maximum number of iteration reached before convergence. Consider increasing max_iter to improve the fit.\n",
            "  ConvergenceWarning)\n",
            "/usr/local/lib/python3.6/dist-packages/sklearn/linear_model/_stochastic_gradient.py:1187: ConvergenceWarning: Maximum number of iteration reached before convergence. Consider increasing max_iter to improve the fit.\n",
            "  ConvergenceWarning)\n",
            "/usr/local/lib/python3.6/dist-packages/sklearn/linear_model/_stochastic_gradient.py:1187: ConvergenceWarning: Maximum number of iteration reached before convergence. Consider increasing max_iter to improve the fit.\n",
            "  ConvergenceWarning)\n",
            "/usr/local/lib/python3.6/dist-packages/sklearn/linear_model/_stochastic_gradient.py:1187: ConvergenceWarning: Maximum number of iteration reached before convergence. Consider increasing max_iter to improve the fit.\n",
            "  ConvergenceWarning)\n",
            "/usr/local/lib/python3.6/dist-packages/sklearn/linear_model/_stochastic_gradient.py:1187: ConvergenceWarning: Maximum number of iteration reached before convergence. Consider increasing max_iter to improve the fit.\n",
            "  ConvergenceWarning)\n",
            "/usr/local/lib/python3.6/dist-packages/sklearn/linear_model/_stochastic_gradient.py:1187: ConvergenceWarning: Maximum number of iteration reached before convergence. Consider increasing max_iter to improve the fit.\n",
            "  ConvergenceWarning)\n",
            "/usr/local/lib/python3.6/dist-packages/sklearn/linear_model/_stochastic_gradient.py:1187: ConvergenceWarning: Maximum number of iteration reached before convergence. Consider increasing max_iter to improve the fit.\n",
            "  ConvergenceWarning)\n",
            "/usr/local/lib/python3.6/dist-packages/sklearn/linear_model/_stochastic_gradient.py:1187: ConvergenceWarning: Maximum number of iteration reached before convergence. Consider increasing max_iter to improve the fit.\n",
            "  ConvergenceWarning)\n",
            "/usr/local/lib/python3.6/dist-packages/sklearn/linear_model/_stochastic_gradient.py:1187: ConvergenceWarning: Maximum number of iteration reached before convergence. Consider increasing max_iter to improve the fit.\n",
            "  ConvergenceWarning)\n",
            "/usr/local/lib/python3.6/dist-packages/sklearn/linear_model/_stochastic_gradient.py:1187: ConvergenceWarning: Maximum number of iteration reached before convergence. Consider increasing max_iter to improve the fit.\n",
            "  ConvergenceWarning)\n",
            "/usr/local/lib/python3.6/dist-packages/sklearn/linear_model/_stochastic_gradient.py:1187: ConvergenceWarning: Maximum number of iteration reached before convergence. Consider increasing max_iter to improve the fit.\n",
            "  ConvergenceWarning)\n",
            "/usr/local/lib/python3.6/dist-packages/sklearn/linear_model/_stochastic_gradient.py:1187: ConvergenceWarning: Maximum number of iteration reached before convergence. Consider increasing max_iter to improve the fit.\n",
            "  ConvergenceWarning)\n",
            "/usr/local/lib/python3.6/dist-packages/sklearn/linear_model/_stochastic_gradient.py:1187: ConvergenceWarning: Maximum number of iteration reached before convergence. Consider increasing max_iter to improve the fit.\n",
            "  ConvergenceWarning)\n",
            "/usr/local/lib/python3.6/dist-packages/sklearn/linear_model/_stochastic_gradient.py:1187: ConvergenceWarning: Maximum number of iteration reached before convergence. Consider increasing max_iter to improve the fit.\n",
            "  ConvergenceWarning)\n",
            "/usr/local/lib/python3.6/dist-packages/sklearn/linear_model/_stochastic_gradient.py:1187: ConvergenceWarning: Maximum number of iteration reached before convergence. Consider increasing max_iter to improve the fit.\n",
            "  ConvergenceWarning)\n",
            "/usr/local/lib/python3.6/dist-packages/sklearn/linear_model/_stochastic_gradient.py:1187: ConvergenceWarning: Maximum number of iteration reached before convergence. Consider increasing max_iter to improve the fit.\n",
            "  ConvergenceWarning)\n",
            "/usr/local/lib/python3.6/dist-packages/sklearn/linear_model/_stochastic_gradient.py:1187: ConvergenceWarning: Maximum number of iteration reached before convergence. Consider increasing max_iter to improve the fit.\n",
            "  ConvergenceWarning)\n",
            "/usr/local/lib/python3.6/dist-packages/sklearn/linear_model/_stochastic_gradient.py:1187: ConvergenceWarning: Maximum number of iteration reached before convergence. Consider increasing max_iter to improve the fit.\n",
            "  ConvergenceWarning)\n",
            "/usr/local/lib/python3.6/dist-packages/sklearn/linear_model/_stochastic_gradient.py:1187: ConvergenceWarning: Maximum number of iteration reached before convergence. Consider increasing max_iter to improve the fit.\n",
            "  ConvergenceWarning)\n",
            "/usr/local/lib/python3.6/dist-packages/sklearn/linear_model/_stochastic_gradient.py:1187: ConvergenceWarning: Maximum number of iteration reached before convergence. Consider increasing max_iter to improve the fit.\n",
            "  ConvergenceWarning)\n",
            "/usr/local/lib/python3.6/dist-packages/sklearn/linear_model/_stochastic_gradient.py:1187: ConvergenceWarning: Maximum number of iteration reached before convergence. Consider increasing max_iter to improve the fit.\n",
            "  ConvergenceWarning)\n",
            "/usr/local/lib/python3.6/dist-packages/sklearn/linear_model/_stochastic_gradient.py:1187: ConvergenceWarning: Maximum number of iteration reached before convergence. Consider increasing max_iter to improve the fit.\n",
            "  ConvergenceWarning)\n",
            "/usr/local/lib/python3.6/dist-packages/sklearn/linear_model/_stochastic_gradient.py:1187: ConvergenceWarning: Maximum number of iteration reached before convergence. Consider increasing max_iter to improve the fit.\n",
            "  ConvergenceWarning)\n",
            "/usr/local/lib/python3.6/dist-packages/sklearn/linear_model/_stochastic_gradient.py:1187: ConvergenceWarning: Maximum number of iteration reached before convergence. Consider increasing max_iter to improve the fit.\n",
            "  ConvergenceWarning)\n",
            "/usr/local/lib/python3.6/dist-packages/sklearn/linear_model/_stochastic_gradient.py:1187: ConvergenceWarning: Maximum number of iteration reached before convergence. Consider increasing max_iter to improve the fit.\n",
            "  ConvergenceWarning)\n",
            "/usr/local/lib/python3.6/dist-packages/sklearn/linear_model/_stochastic_gradient.py:1187: ConvergenceWarning: Maximum number of iteration reached before convergence. Consider increasing max_iter to improve the fit.\n",
            "  ConvergenceWarning)\n",
            "/usr/local/lib/python3.6/dist-packages/sklearn/linear_model/_stochastic_gradient.py:1187: ConvergenceWarning: Maximum number of iteration reached before convergence. Consider increasing max_iter to improve the fit.\n",
            "  ConvergenceWarning)\n",
            "/usr/local/lib/python3.6/dist-packages/sklearn/linear_model/_stochastic_gradient.py:1187: ConvergenceWarning: Maximum number of iteration reached before convergence. Consider increasing max_iter to improve the fit.\n",
            "  ConvergenceWarning)\n",
            "/usr/local/lib/python3.6/dist-packages/sklearn/linear_model/_stochastic_gradient.py:1187: ConvergenceWarning: Maximum number of iteration reached before convergence. Consider increasing max_iter to improve the fit.\n",
            "  ConvergenceWarning)\n",
            "/usr/local/lib/python3.6/dist-packages/sklearn/linear_model/_stochastic_gradient.py:1187: ConvergenceWarning: Maximum number of iteration reached before convergence. Consider increasing max_iter to improve the fit.\n",
            "  ConvergenceWarning)\n",
            "/usr/local/lib/python3.6/dist-packages/sklearn/linear_model/_stochastic_gradient.py:1187: ConvergenceWarning: Maximum number of iteration reached before convergence. Consider increasing max_iter to improve the fit.\n",
            "  ConvergenceWarning)\n",
            "/usr/local/lib/python3.6/dist-packages/sklearn/linear_model/_stochastic_gradient.py:1187: ConvergenceWarning: Maximum number of iteration reached before convergence. Consider increasing max_iter to improve the fit.\n",
            "  ConvergenceWarning)\n",
            "/usr/local/lib/python3.6/dist-packages/sklearn/linear_model/_stochastic_gradient.py:1187: ConvergenceWarning: Maximum number of iteration reached before convergence. Consider increasing max_iter to improve the fit.\n",
            "  ConvergenceWarning)\n",
            "/usr/local/lib/python3.6/dist-packages/sklearn/linear_model/_stochastic_gradient.py:1187: ConvergenceWarning: Maximum number of iteration reached before convergence. Consider increasing max_iter to improve the fit.\n",
            "  ConvergenceWarning)\n",
            "/usr/local/lib/python3.6/dist-packages/sklearn/linear_model/_stochastic_gradient.py:1187: ConvergenceWarning: Maximum number of iteration reached before convergence. Consider increasing max_iter to improve the fit.\n",
            "  ConvergenceWarning)\n",
            "/usr/local/lib/python3.6/dist-packages/sklearn/linear_model/_stochastic_gradient.py:1187: ConvergenceWarning: Maximum number of iteration reached before convergence. Consider increasing max_iter to improve the fit.\n",
            "  ConvergenceWarning)\n",
            "/usr/local/lib/python3.6/dist-packages/sklearn/linear_model/_stochastic_gradient.py:1187: ConvergenceWarning: Maximum number of iteration reached before convergence. Consider increasing max_iter to improve the fit.\n",
            "  ConvergenceWarning)\n",
            "/usr/local/lib/python3.6/dist-packages/sklearn/linear_model/_stochastic_gradient.py:1187: ConvergenceWarning: Maximum number of iteration reached before convergence. Consider increasing max_iter to improve the fit.\n",
            "  ConvergenceWarning)\n",
            "/usr/local/lib/python3.6/dist-packages/sklearn/linear_model/_stochastic_gradient.py:1187: ConvergenceWarning: Maximum number of iteration reached before convergence. Consider increasing max_iter to improve the fit.\n",
            "  ConvergenceWarning)\n",
            "/usr/local/lib/python3.6/dist-packages/sklearn/linear_model/_stochastic_gradient.py:1187: ConvergenceWarning: Maximum number of iteration reached before convergence. Consider increasing max_iter to improve the fit.\n",
            "  ConvergenceWarning)\n",
            "/usr/local/lib/python3.6/dist-packages/sklearn/linear_model/_stochastic_gradient.py:1187: ConvergenceWarning: Maximum number of iteration reached before convergence. Consider increasing max_iter to improve the fit.\n",
            "  ConvergenceWarning)\n",
            "/usr/local/lib/python3.6/dist-packages/sklearn/linear_model/_stochastic_gradient.py:1187: ConvergenceWarning: Maximum number of iteration reached before convergence. Consider increasing max_iter to improve the fit.\n",
            "  ConvergenceWarning)\n",
            "/usr/local/lib/python3.6/dist-packages/sklearn/linear_model/_stochastic_gradient.py:1187: ConvergenceWarning: Maximum number of iteration reached before convergence. Consider increasing max_iter to improve the fit.\n",
            "  ConvergenceWarning)\n",
            "/usr/local/lib/python3.6/dist-packages/sklearn/linear_model/_stochastic_gradient.py:1187: ConvergenceWarning: Maximum number of iteration reached before convergence. Consider increasing max_iter to improve the fit.\n",
            "  ConvergenceWarning)\n",
            "/usr/local/lib/python3.6/dist-packages/sklearn/linear_model/_stochastic_gradient.py:1187: ConvergenceWarning: Maximum number of iteration reached before convergence. Consider increasing max_iter to improve the fit.\n",
            "  ConvergenceWarning)\n",
            "/usr/local/lib/python3.6/dist-packages/sklearn/linear_model/_stochastic_gradient.py:1187: ConvergenceWarning: Maximum number of iteration reached before convergence. Consider increasing max_iter to improve the fit.\n",
            "  ConvergenceWarning)\n",
            "/usr/local/lib/python3.6/dist-packages/sklearn/linear_model/_stochastic_gradient.py:1187: ConvergenceWarning: Maximum number of iteration reached before convergence. Consider increasing max_iter to improve the fit.\n",
            "  ConvergenceWarning)\n",
            "/usr/local/lib/python3.6/dist-packages/sklearn/linear_model/_stochastic_gradient.py:1187: ConvergenceWarning: Maximum number of iteration reached before convergence. Consider increasing max_iter to improve the fit.\n",
            "  ConvergenceWarning)\n",
            "/usr/local/lib/python3.6/dist-packages/sklearn/linear_model/_stochastic_gradient.py:1187: ConvergenceWarning: Maximum number of iteration reached before convergence. Consider increasing max_iter to improve the fit.\n",
            "  ConvergenceWarning)\n",
            "/usr/local/lib/python3.6/dist-packages/sklearn/linear_model/_stochastic_gradient.py:1187: ConvergenceWarning: Maximum number of iteration reached before convergence. Consider increasing max_iter to improve the fit.\n",
            "  ConvergenceWarning)\n",
            "/usr/local/lib/python3.6/dist-packages/sklearn/linear_model/_stochastic_gradient.py:1187: ConvergenceWarning: Maximum number of iteration reached before convergence. Consider increasing max_iter to improve the fit.\n",
            "  ConvergenceWarning)\n",
            "/usr/local/lib/python3.6/dist-packages/sklearn/linear_model/_stochastic_gradient.py:1187: ConvergenceWarning: Maximum number of iteration reached before convergence. Consider increasing max_iter to improve the fit.\n",
            "  ConvergenceWarning)\n",
            "/usr/local/lib/python3.6/dist-packages/sklearn/linear_model/_stochastic_gradient.py:1187: ConvergenceWarning: Maximum number of iteration reached before convergence. Consider increasing max_iter to improve the fit.\n",
            "  ConvergenceWarning)\n",
            "/usr/local/lib/python3.6/dist-packages/sklearn/linear_model/_stochastic_gradient.py:1187: ConvergenceWarning: Maximum number of iteration reached before convergence. Consider increasing max_iter to improve the fit.\n",
            "  ConvergenceWarning)\n",
            "/usr/local/lib/python3.6/dist-packages/sklearn/linear_model/_stochastic_gradient.py:1187: ConvergenceWarning: Maximum number of iteration reached before convergence. Consider increasing max_iter to improve the fit.\n",
            "  ConvergenceWarning)\n",
            "/usr/local/lib/python3.6/dist-packages/sklearn/linear_model/_stochastic_gradient.py:1187: ConvergenceWarning: Maximum number of iteration reached before convergence. Consider increasing max_iter to improve the fit.\n",
            "  ConvergenceWarning)\n",
            "/usr/local/lib/python3.6/dist-packages/sklearn/linear_model/_stochastic_gradient.py:1187: ConvergenceWarning: Maximum number of iteration reached before convergence. Consider increasing max_iter to improve the fit.\n",
            "  ConvergenceWarning)\n",
            "/usr/local/lib/python3.6/dist-packages/sklearn/linear_model/_stochastic_gradient.py:1187: ConvergenceWarning: Maximum number of iteration reached before convergence. Consider increasing max_iter to improve the fit.\n",
            "  ConvergenceWarning)\n",
            "/usr/local/lib/python3.6/dist-packages/sklearn/linear_model/_stochastic_gradient.py:1187: ConvergenceWarning: Maximum number of iteration reached before convergence. Consider increasing max_iter to improve the fit.\n",
            "  ConvergenceWarning)\n",
            "/usr/local/lib/python3.6/dist-packages/sklearn/linear_model/_stochastic_gradient.py:1187: ConvergenceWarning: Maximum number of iteration reached before convergence. Consider increasing max_iter to improve the fit.\n",
            "  ConvergenceWarning)\n",
            "/usr/local/lib/python3.6/dist-packages/sklearn/linear_model/_stochastic_gradient.py:1187: ConvergenceWarning: Maximum number of iteration reached before convergence. Consider increasing max_iter to improve the fit.\n",
            "  ConvergenceWarning)\n",
            "/usr/local/lib/python3.6/dist-packages/sklearn/linear_model/_stochastic_gradient.py:1187: ConvergenceWarning: Maximum number of iteration reached before convergence. Consider increasing max_iter to improve the fit.\n",
            "  ConvergenceWarning)\n",
            "/usr/local/lib/python3.6/dist-packages/sklearn/linear_model/_stochastic_gradient.py:1187: ConvergenceWarning: Maximum number of iteration reached before convergence. Consider increasing max_iter to improve the fit.\n",
            "  ConvergenceWarning)\n",
            "/usr/local/lib/python3.6/dist-packages/sklearn/linear_model/_stochastic_gradient.py:1187: ConvergenceWarning: Maximum number of iteration reached before convergence. Consider increasing max_iter to improve the fit.\n",
            "  ConvergenceWarning)\n",
            "/usr/local/lib/python3.6/dist-packages/sklearn/linear_model/_stochastic_gradient.py:1187: ConvergenceWarning: Maximum number of iteration reached before convergence. Consider increasing max_iter to improve the fit.\n",
            "  ConvergenceWarning)\n",
            "/usr/local/lib/python3.6/dist-packages/sklearn/linear_model/_stochastic_gradient.py:1187: ConvergenceWarning: Maximum number of iteration reached before convergence. Consider increasing max_iter to improve the fit.\n",
            "  ConvergenceWarning)\n",
            "/usr/local/lib/python3.6/dist-packages/sklearn/linear_model/_stochastic_gradient.py:1187: ConvergenceWarning: Maximum number of iteration reached before convergence. Consider increasing max_iter to improve the fit.\n",
            "  ConvergenceWarning)\n",
            "/usr/local/lib/python3.6/dist-packages/sklearn/linear_model/_stochastic_gradient.py:1187: ConvergenceWarning: Maximum number of iteration reached before convergence. Consider increasing max_iter to improve the fit.\n",
            "  ConvergenceWarning)\n",
            "/usr/local/lib/python3.6/dist-packages/sklearn/linear_model/_stochastic_gradient.py:1187: ConvergenceWarning: Maximum number of iteration reached before convergence. Consider increasing max_iter to improve the fit.\n",
            "  ConvergenceWarning)\n",
            "/usr/local/lib/python3.6/dist-packages/sklearn/linear_model/_stochastic_gradient.py:1187: ConvergenceWarning: Maximum number of iteration reached before convergence. Consider increasing max_iter to improve the fit.\n",
            "  ConvergenceWarning)\n",
            "/usr/local/lib/python3.6/dist-packages/sklearn/linear_model/_stochastic_gradient.py:1187: ConvergenceWarning: Maximum number of iteration reached before convergence. Consider increasing max_iter to improve the fit.\n",
            "  ConvergenceWarning)\n",
            "/usr/local/lib/python3.6/dist-packages/sklearn/linear_model/_stochastic_gradient.py:1187: ConvergenceWarning: Maximum number of iteration reached before convergence. Consider increasing max_iter to improve the fit.\n",
            "  ConvergenceWarning)\n",
            "/usr/local/lib/python3.6/dist-packages/sklearn/linear_model/_stochastic_gradient.py:1187: ConvergenceWarning: Maximum number of iteration reached before convergence. Consider increasing max_iter to improve the fit.\n",
            "  ConvergenceWarning)\n",
            "/usr/local/lib/python3.6/dist-packages/sklearn/linear_model/_stochastic_gradient.py:1187: ConvergenceWarning: Maximum number of iteration reached before convergence. Consider increasing max_iter to improve the fit.\n",
            "  ConvergenceWarning)\n",
            "/usr/local/lib/python3.6/dist-packages/sklearn/linear_model/_stochastic_gradient.py:1187: ConvergenceWarning: Maximum number of iteration reached before convergence. Consider increasing max_iter to improve the fit.\n",
            "  ConvergenceWarning)\n",
            "/usr/local/lib/python3.6/dist-packages/sklearn/linear_model/_stochastic_gradient.py:1187: ConvergenceWarning: Maximum number of iteration reached before convergence. Consider increasing max_iter to improve the fit.\n",
            "  ConvergenceWarning)\n",
            "/usr/local/lib/python3.6/dist-packages/sklearn/linear_model/_stochastic_gradient.py:1187: ConvergenceWarning: Maximum number of iteration reached before convergence. Consider increasing max_iter to improve the fit.\n",
            "  ConvergenceWarning)\n",
            "/usr/local/lib/python3.6/dist-packages/sklearn/linear_model/_stochastic_gradient.py:1187: ConvergenceWarning: Maximum number of iteration reached before convergence. Consider increasing max_iter to improve the fit.\n",
            "  ConvergenceWarning)\n",
            "/usr/local/lib/python3.6/dist-packages/sklearn/linear_model/_stochastic_gradient.py:1187: ConvergenceWarning: Maximum number of iteration reached before convergence. Consider increasing max_iter to improve the fit.\n",
            "  ConvergenceWarning)\n",
            "/usr/local/lib/python3.6/dist-packages/sklearn/linear_model/_stochastic_gradient.py:1187: ConvergenceWarning: Maximum number of iteration reached before convergence. Consider increasing max_iter to improve the fit.\n",
            "  ConvergenceWarning)\n",
            "/usr/local/lib/python3.6/dist-packages/sklearn/linear_model/_stochastic_gradient.py:1187: ConvergenceWarning: Maximum number of iteration reached before convergence. Consider increasing max_iter to improve the fit.\n",
            "  ConvergenceWarning)\n",
            "/usr/local/lib/python3.6/dist-packages/sklearn/linear_model/_stochastic_gradient.py:1187: ConvergenceWarning: Maximum number of iteration reached before convergence. Consider increasing max_iter to improve the fit.\n",
            "  ConvergenceWarning)\n",
            "/usr/local/lib/python3.6/dist-packages/sklearn/linear_model/_stochastic_gradient.py:1187: ConvergenceWarning: Maximum number of iteration reached before convergence. Consider increasing max_iter to improve the fit.\n",
            "  ConvergenceWarning)\n",
            "/usr/local/lib/python3.6/dist-packages/sklearn/linear_model/_stochastic_gradient.py:1187: ConvergenceWarning: Maximum number of iteration reached before convergence. Consider increasing max_iter to improve the fit.\n",
            "  ConvergenceWarning)\n",
            "/usr/local/lib/python3.6/dist-packages/sklearn/linear_model/_stochastic_gradient.py:1187: ConvergenceWarning: Maximum number of iteration reached before convergence. Consider increasing max_iter to improve the fit.\n",
            "  ConvergenceWarning)\n",
            "/usr/local/lib/python3.6/dist-packages/sklearn/linear_model/_stochastic_gradient.py:1187: ConvergenceWarning: Maximum number of iteration reached before convergence. Consider increasing max_iter to improve the fit.\n",
            "  ConvergenceWarning)\n",
            "/usr/local/lib/python3.6/dist-packages/sklearn/linear_model/_stochastic_gradient.py:1187: ConvergenceWarning: Maximum number of iteration reached before convergence. Consider increasing max_iter to improve the fit.\n",
            "  ConvergenceWarning)\n",
            "/usr/local/lib/python3.6/dist-packages/sklearn/linear_model/_stochastic_gradient.py:1187: ConvergenceWarning: Maximum number of iteration reached before convergence. Consider increasing max_iter to improve the fit.\n",
            "  ConvergenceWarning)\n",
            "/usr/local/lib/python3.6/dist-packages/sklearn/linear_model/_stochastic_gradient.py:1187: ConvergenceWarning: Maximum number of iteration reached before convergence. Consider increasing max_iter to improve the fit.\n",
            "  ConvergenceWarning)\n",
            "/usr/local/lib/python3.6/dist-packages/sklearn/linear_model/_stochastic_gradient.py:1187: ConvergenceWarning: Maximum number of iteration reached before convergence. Consider increasing max_iter to improve the fit.\n",
            "  ConvergenceWarning)\n",
            "/usr/local/lib/python3.6/dist-packages/sklearn/linear_model/_stochastic_gradient.py:1187: ConvergenceWarning: Maximum number of iteration reached before convergence. Consider increasing max_iter to improve the fit.\n",
            "  ConvergenceWarning)\n",
            "/usr/local/lib/python3.6/dist-packages/sklearn/linear_model/_stochastic_gradient.py:1187: ConvergenceWarning: Maximum number of iteration reached before convergence. Consider increasing max_iter to improve the fit.\n",
            "  ConvergenceWarning)\n",
            "/usr/local/lib/python3.6/dist-packages/sklearn/linear_model/_stochastic_gradient.py:1187: ConvergenceWarning: Maximum number of iteration reached before convergence. Consider increasing max_iter to improve the fit.\n",
            "  ConvergenceWarning)\n",
            "/usr/local/lib/python3.6/dist-packages/sklearn/linear_model/_stochastic_gradient.py:1187: ConvergenceWarning: Maximum number of iteration reached before convergence. Consider increasing max_iter to improve the fit.\n",
            "  ConvergenceWarning)\n",
            "/usr/local/lib/python3.6/dist-packages/sklearn/linear_model/_stochastic_gradient.py:1187: ConvergenceWarning: Maximum number of iteration reached before convergence. Consider increasing max_iter to improve the fit.\n",
            "  ConvergenceWarning)\n",
            "/usr/local/lib/python3.6/dist-packages/sklearn/linear_model/_stochastic_gradient.py:1187: ConvergenceWarning: Maximum number of iteration reached before convergence. Consider increasing max_iter to improve the fit.\n",
            "  ConvergenceWarning)\n",
            "/usr/local/lib/python3.6/dist-packages/sklearn/linear_model/_stochastic_gradient.py:1187: ConvergenceWarning: Maximum number of iteration reached before convergence. Consider increasing max_iter to improve the fit.\n",
            "  ConvergenceWarning)\n",
            "/usr/local/lib/python3.6/dist-packages/sklearn/linear_model/_stochastic_gradient.py:1187: ConvergenceWarning: Maximum number of iteration reached before convergence. Consider increasing max_iter to improve the fit.\n",
            "  ConvergenceWarning)\n",
            "/usr/local/lib/python3.6/dist-packages/sklearn/linear_model/_stochastic_gradient.py:1187: ConvergenceWarning: Maximum number of iteration reached before convergence. Consider increasing max_iter to improve the fit.\n",
            "  ConvergenceWarning)\n",
            "/usr/local/lib/python3.6/dist-packages/sklearn/linear_model/_stochastic_gradient.py:1187: ConvergenceWarning: Maximum number of iteration reached before convergence. Consider increasing max_iter to improve the fit.\n",
            "  ConvergenceWarning)\n",
            "/usr/local/lib/python3.6/dist-packages/sklearn/linear_model/_stochastic_gradient.py:1187: ConvergenceWarning: Maximum number of iteration reached before convergence. Consider increasing max_iter to improve the fit.\n",
            "  ConvergenceWarning)\n",
            "/usr/local/lib/python3.6/dist-packages/sklearn/linear_model/_stochastic_gradient.py:1187: ConvergenceWarning: Maximum number of iteration reached before convergence. Consider increasing max_iter to improve the fit.\n",
            "  ConvergenceWarning)\n",
            "/usr/local/lib/python3.6/dist-packages/sklearn/linear_model/_stochastic_gradient.py:1187: ConvergenceWarning: Maximum number of iteration reached before convergence. Consider increasing max_iter to improve the fit.\n",
            "  ConvergenceWarning)\n",
            "/usr/local/lib/python3.6/dist-packages/sklearn/linear_model/_stochastic_gradient.py:1187: ConvergenceWarning: Maximum number of iteration reached before convergence. Consider increasing max_iter to improve the fit.\n",
            "  ConvergenceWarning)\n",
            "/usr/local/lib/python3.6/dist-packages/sklearn/linear_model/_stochastic_gradient.py:1187: ConvergenceWarning: Maximum number of iteration reached before convergence. Consider increasing max_iter to improve the fit.\n",
            "  ConvergenceWarning)\n",
            "/usr/local/lib/python3.6/dist-packages/sklearn/linear_model/_stochastic_gradient.py:1187: ConvergenceWarning: Maximum number of iteration reached before convergence. Consider increasing max_iter to improve the fit.\n",
            "  ConvergenceWarning)\n",
            "/usr/local/lib/python3.6/dist-packages/sklearn/linear_model/_stochastic_gradient.py:1187: ConvergenceWarning: Maximum number of iteration reached before convergence. Consider increasing max_iter to improve the fit.\n",
            "  ConvergenceWarning)\n",
            "/usr/local/lib/python3.6/dist-packages/sklearn/linear_model/_stochastic_gradient.py:1187: ConvergenceWarning: Maximum number of iteration reached before convergence. Consider increasing max_iter to improve the fit.\n",
            "  ConvergenceWarning)\n",
            "/usr/local/lib/python3.6/dist-packages/sklearn/linear_model/_stochastic_gradient.py:1187: ConvergenceWarning: Maximum number of iteration reached before convergence. Consider increasing max_iter to improve the fit.\n",
            "  ConvergenceWarning)\n",
            "/usr/local/lib/python3.6/dist-packages/sklearn/linear_model/_stochastic_gradient.py:1187: ConvergenceWarning: Maximum number of iteration reached before convergence. Consider increasing max_iter to improve the fit.\n",
            "  ConvergenceWarning)\n",
            "/usr/local/lib/python3.6/dist-packages/sklearn/linear_model/_stochastic_gradient.py:1187: ConvergenceWarning: Maximum number of iteration reached before convergence. Consider increasing max_iter to improve the fit.\n",
            "  ConvergenceWarning)\n",
            "/usr/local/lib/python3.6/dist-packages/sklearn/linear_model/_stochastic_gradient.py:1187: ConvergenceWarning: Maximum number of iteration reached before convergence. Consider increasing max_iter to improve the fit.\n",
            "  ConvergenceWarning)\n",
            "/usr/local/lib/python3.6/dist-packages/sklearn/linear_model/_stochastic_gradient.py:1187: ConvergenceWarning: Maximum number of iteration reached before convergence. Consider increasing max_iter to improve the fit.\n",
            "  ConvergenceWarning)\n",
            "/usr/local/lib/python3.6/dist-packages/sklearn/linear_model/_stochastic_gradient.py:1187: ConvergenceWarning: Maximum number of iteration reached before convergence. Consider increasing max_iter to improve the fit.\n",
            "  ConvergenceWarning)\n",
            "/usr/local/lib/python3.6/dist-packages/sklearn/linear_model/_stochastic_gradient.py:1187: ConvergenceWarning: Maximum number of iteration reached before convergence. Consider increasing max_iter to improve the fit.\n",
            "  ConvergenceWarning)\n",
            "/usr/local/lib/python3.6/dist-packages/sklearn/linear_model/_stochastic_gradient.py:1187: ConvergenceWarning: Maximum number of iteration reached before convergence. Consider increasing max_iter to improve the fit.\n",
            "  ConvergenceWarning)\n",
            "/usr/local/lib/python3.6/dist-packages/sklearn/linear_model/_stochastic_gradient.py:1187: ConvergenceWarning: Maximum number of iteration reached before convergence. Consider increasing max_iter to improve the fit.\n",
            "  ConvergenceWarning)\n",
            "/usr/local/lib/python3.6/dist-packages/sklearn/linear_model/_stochastic_gradient.py:1187: ConvergenceWarning: Maximum number of iteration reached before convergence. Consider increasing max_iter to improve the fit.\n",
            "  ConvergenceWarning)\n",
            "/usr/local/lib/python3.6/dist-packages/sklearn/linear_model/_stochastic_gradient.py:1187: ConvergenceWarning: Maximum number of iteration reached before convergence. Consider increasing max_iter to improve the fit.\n",
            "  ConvergenceWarning)\n",
            "/usr/local/lib/python3.6/dist-packages/sklearn/linear_model/_stochastic_gradient.py:1187: ConvergenceWarning: Maximum number of iteration reached before convergence. Consider increasing max_iter to improve the fit.\n",
            "  ConvergenceWarning)\n",
            "/usr/local/lib/python3.6/dist-packages/sklearn/linear_model/_stochastic_gradient.py:1187: ConvergenceWarning: Maximum number of iteration reached before convergence. Consider increasing max_iter to improve the fit.\n",
            "  ConvergenceWarning)\n",
            "/usr/local/lib/python3.6/dist-packages/sklearn/linear_model/_stochastic_gradient.py:1187: ConvergenceWarning: Maximum number of iteration reached before convergence. Consider increasing max_iter to improve the fit.\n",
            "  ConvergenceWarning)\n",
            "/usr/local/lib/python3.6/dist-packages/sklearn/linear_model/_stochastic_gradient.py:1187: ConvergenceWarning: Maximum number of iteration reached before convergence. Consider increasing max_iter to improve the fit.\n",
            "  ConvergenceWarning)\n",
            "/usr/local/lib/python3.6/dist-packages/sklearn/linear_model/_stochastic_gradient.py:1187: ConvergenceWarning: Maximum number of iteration reached before convergence. Consider increasing max_iter to improve the fit.\n",
            "  ConvergenceWarning)\n",
            "/usr/local/lib/python3.6/dist-packages/sklearn/linear_model/_stochastic_gradient.py:1187: ConvergenceWarning: Maximum number of iteration reached before convergence. Consider increasing max_iter to improve the fit.\n",
            "  ConvergenceWarning)\n",
            "/usr/local/lib/python3.6/dist-packages/sklearn/linear_model/_stochastic_gradient.py:1187: ConvergenceWarning: Maximum number of iteration reached before convergence. Consider increasing max_iter to improve the fit.\n",
            "  ConvergenceWarning)\n",
            "/usr/local/lib/python3.6/dist-packages/sklearn/linear_model/_stochastic_gradient.py:1187: ConvergenceWarning: Maximum number of iteration reached before convergence. Consider increasing max_iter to improve the fit.\n",
            "  ConvergenceWarning)\n",
            "/usr/local/lib/python3.6/dist-packages/sklearn/linear_model/_stochastic_gradient.py:1187: ConvergenceWarning: Maximum number of iteration reached before convergence. Consider increasing max_iter to improve the fit.\n",
            "  ConvergenceWarning)\n",
            "/usr/local/lib/python3.6/dist-packages/sklearn/linear_model/_stochastic_gradient.py:1187: ConvergenceWarning: Maximum number of iteration reached before convergence. Consider increasing max_iter to improve the fit.\n",
            "  ConvergenceWarning)\n",
            "/usr/local/lib/python3.6/dist-packages/sklearn/linear_model/_stochastic_gradient.py:1187: ConvergenceWarning: Maximum number of iteration reached before convergence. Consider increasing max_iter to improve the fit.\n",
            "  ConvergenceWarning)\n",
            "/usr/local/lib/python3.6/dist-packages/sklearn/linear_model/_stochastic_gradient.py:1187: ConvergenceWarning: Maximum number of iteration reached before convergence. Consider increasing max_iter to improve the fit.\n",
            "  ConvergenceWarning)\n",
            "/usr/local/lib/python3.6/dist-packages/sklearn/linear_model/_stochastic_gradient.py:1187: ConvergenceWarning: Maximum number of iteration reached before convergence. Consider increasing max_iter to improve the fit.\n",
            "  ConvergenceWarning)\n",
            "/usr/local/lib/python3.6/dist-packages/sklearn/linear_model/_stochastic_gradient.py:1187: ConvergenceWarning: Maximum number of iteration reached before convergence. Consider increasing max_iter to improve the fit.\n",
            "  ConvergenceWarning)\n",
            "/usr/local/lib/python3.6/dist-packages/sklearn/linear_model/_stochastic_gradient.py:1187: ConvergenceWarning: Maximum number of iteration reached before convergence. Consider increasing max_iter to improve the fit.\n",
            "  ConvergenceWarning)\n",
            "/usr/local/lib/python3.6/dist-packages/sklearn/linear_model/_stochastic_gradient.py:1187: ConvergenceWarning: Maximum number of iteration reached before convergence. Consider increasing max_iter to improve the fit.\n",
            "  ConvergenceWarning)\n",
            "/usr/local/lib/python3.6/dist-packages/sklearn/linear_model/_stochastic_gradient.py:1187: ConvergenceWarning: Maximum number of iteration reached before convergence. Consider increasing max_iter to improve the fit.\n",
            "  ConvergenceWarning)\n",
            "/usr/local/lib/python3.6/dist-packages/sklearn/linear_model/_stochastic_gradient.py:1187: ConvergenceWarning: Maximum number of iteration reached before convergence. Consider increasing max_iter to improve the fit.\n",
            "  ConvergenceWarning)\n",
            "/usr/local/lib/python3.6/dist-packages/sklearn/linear_model/_stochastic_gradient.py:1187: ConvergenceWarning: Maximum number of iteration reached before convergence. Consider increasing max_iter to improve the fit.\n",
            "  ConvergenceWarning)\n",
            "/usr/local/lib/python3.6/dist-packages/sklearn/linear_model/_stochastic_gradient.py:1187: ConvergenceWarning: Maximum number of iteration reached before convergence. Consider increasing max_iter to improve the fit.\n",
            "  ConvergenceWarning)\n",
            "/usr/local/lib/python3.6/dist-packages/sklearn/linear_model/_stochastic_gradient.py:1187: ConvergenceWarning: Maximum number of iteration reached before convergence. Consider increasing max_iter to improve the fit.\n",
            "  ConvergenceWarning)\n",
            "/usr/local/lib/python3.6/dist-packages/sklearn/linear_model/_stochastic_gradient.py:1187: ConvergenceWarning: Maximum number of iteration reached before convergence. Consider increasing max_iter to improve the fit.\n",
            "  ConvergenceWarning)\n",
            "/usr/local/lib/python3.6/dist-packages/sklearn/linear_model/_stochastic_gradient.py:1187: ConvergenceWarning: Maximum number of iteration reached before convergence. Consider increasing max_iter to improve the fit.\n",
            "  ConvergenceWarning)\n",
            "/usr/local/lib/python3.6/dist-packages/sklearn/linear_model/_stochastic_gradient.py:1187: ConvergenceWarning: Maximum number of iteration reached before convergence. Consider increasing max_iter to improve the fit.\n",
            "  ConvergenceWarning)\n",
            "/usr/local/lib/python3.6/dist-packages/sklearn/linear_model/_stochastic_gradient.py:1187: ConvergenceWarning: Maximum number of iteration reached before convergence. Consider increasing max_iter to improve the fit.\n",
            "  ConvergenceWarning)\n",
            "/usr/local/lib/python3.6/dist-packages/sklearn/linear_model/_stochastic_gradient.py:1187: ConvergenceWarning: Maximum number of iteration reached before convergence. Consider increasing max_iter to improve the fit.\n",
            "  ConvergenceWarning)\n",
            "/usr/local/lib/python3.6/dist-packages/sklearn/linear_model/_stochastic_gradient.py:1187: ConvergenceWarning: Maximum number of iteration reached before convergence. Consider increasing max_iter to improve the fit.\n",
            "  ConvergenceWarning)\n",
            "/usr/local/lib/python3.6/dist-packages/sklearn/linear_model/_stochastic_gradient.py:1187: ConvergenceWarning: Maximum number of iteration reached before convergence. Consider increasing max_iter to improve the fit.\n",
            "  ConvergenceWarning)\n",
            "/usr/local/lib/python3.6/dist-packages/sklearn/linear_model/_stochastic_gradient.py:1187: ConvergenceWarning: Maximum number of iteration reached before convergence. Consider increasing max_iter to improve the fit.\n",
            "  ConvergenceWarning)\n",
            "/usr/local/lib/python3.6/dist-packages/sklearn/linear_model/_stochastic_gradient.py:1187: ConvergenceWarning: Maximum number of iteration reached before convergence. Consider increasing max_iter to improve the fit.\n",
            "  ConvergenceWarning)\n",
            "/usr/local/lib/python3.6/dist-packages/sklearn/linear_model/_stochastic_gradient.py:1187: ConvergenceWarning: Maximum number of iteration reached before convergence. Consider increasing max_iter to improve the fit.\n",
            "  ConvergenceWarning)\n",
            "/usr/local/lib/python3.6/dist-packages/sklearn/linear_model/_stochastic_gradient.py:1187: ConvergenceWarning: Maximum number of iteration reached before convergence. Consider increasing max_iter to improve the fit.\n",
            "  ConvergenceWarning)\n",
            "/usr/local/lib/python3.6/dist-packages/sklearn/linear_model/_stochastic_gradient.py:1187: ConvergenceWarning: Maximum number of iteration reached before convergence. Consider increasing max_iter to improve the fit.\n",
            "  ConvergenceWarning)\n",
            "/usr/local/lib/python3.6/dist-packages/sklearn/linear_model/_stochastic_gradient.py:1187: ConvergenceWarning: Maximum number of iteration reached before convergence. Consider increasing max_iter to improve the fit.\n",
            "  ConvergenceWarning)\n",
            "/usr/local/lib/python3.6/dist-packages/sklearn/linear_model/_stochastic_gradient.py:1187: ConvergenceWarning: Maximum number of iteration reached before convergence. Consider increasing max_iter to improve the fit.\n",
            "  ConvergenceWarning)\n",
            "/usr/local/lib/python3.6/dist-packages/sklearn/linear_model/_stochastic_gradient.py:1187: ConvergenceWarning: Maximum number of iteration reached before convergence. Consider increasing max_iter to improve the fit.\n",
            "  ConvergenceWarning)\n",
            "/usr/local/lib/python3.6/dist-packages/sklearn/linear_model/_stochastic_gradient.py:1187: ConvergenceWarning: Maximum number of iteration reached before convergence. Consider increasing max_iter to improve the fit.\n",
            "  ConvergenceWarning)\n",
            "/usr/local/lib/python3.6/dist-packages/sklearn/linear_model/_stochastic_gradient.py:1187: ConvergenceWarning: Maximum number of iteration reached before convergence. Consider increasing max_iter to improve the fit.\n",
            "  ConvergenceWarning)\n",
            "/usr/local/lib/python3.6/dist-packages/sklearn/linear_model/_stochastic_gradient.py:1187: ConvergenceWarning: Maximum number of iteration reached before convergence. Consider increasing max_iter to improve the fit.\n",
            "  ConvergenceWarning)\n",
            "/usr/local/lib/python3.6/dist-packages/sklearn/linear_model/_stochastic_gradient.py:1187: ConvergenceWarning: Maximum number of iteration reached before convergence. Consider increasing max_iter to improve the fit.\n",
            "  ConvergenceWarning)\n",
            "/usr/local/lib/python3.6/dist-packages/sklearn/linear_model/_stochastic_gradient.py:1187: ConvergenceWarning: Maximum number of iteration reached before convergence. Consider increasing max_iter to improve the fit.\n",
            "  ConvergenceWarning)\n",
            "/usr/local/lib/python3.6/dist-packages/sklearn/linear_model/_stochastic_gradient.py:1187: ConvergenceWarning: Maximum number of iteration reached before convergence. Consider increasing max_iter to improve the fit.\n",
            "  ConvergenceWarning)\n",
            "/usr/local/lib/python3.6/dist-packages/sklearn/linear_model/_stochastic_gradient.py:1187: ConvergenceWarning: Maximum number of iteration reached before convergence. Consider increasing max_iter to improve the fit.\n",
            "  ConvergenceWarning)\n",
            "/usr/local/lib/python3.6/dist-packages/sklearn/linear_model/_stochastic_gradient.py:1187: ConvergenceWarning: Maximum number of iteration reached before convergence. Consider increasing max_iter to improve the fit.\n",
            "  ConvergenceWarning)\n",
            "/usr/local/lib/python3.6/dist-packages/sklearn/linear_model/_stochastic_gradient.py:1187: ConvergenceWarning: Maximum number of iteration reached before convergence. Consider increasing max_iter to improve the fit.\n",
            "  ConvergenceWarning)\n",
            "/usr/local/lib/python3.6/dist-packages/sklearn/linear_model/_stochastic_gradient.py:1187: ConvergenceWarning: Maximum number of iteration reached before convergence. Consider increasing max_iter to improve the fit.\n",
            "  ConvergenceWarning)\n",
            "/usr/local/lib/python3.6/dist-packages/sklearn/linear_model/_stochastic_gradient.py:1187: ConvergenceWarning: Maximum number of iteration reached before convergence. Consider increasing max_iter to improve the fit.\n",
            "  ConvergenceWarning)\n",
            "/usr/local/lib/python3.6/dist-packages/sklearn/linear_model/_stochastic_gradient.py:1187: ConvergenceWarning: Maximum number of iteration reached before convergence. Consider increasing max_iter to improve the fit.\n",
            "  ConvergenceWarning)\n",
            "/usr/local/lib/python3.6/dist-packages/sklearn/linear_model/_stochastic_gradient.py:1187: ConvergenceWarning: Maximum number of iteration reached before convergence. Consider increasing max_iter to improve the fit.\n",
            "  ConvergenceWarning)\n",
            "/usr/local/lib/python3.6/dist-packages/sklearn/linear_model/_stochastic_gradient.py:1187: ConvergenceWarning: Maximum number of iteration reached before convergence. Consider increasing max_iter to improve the fit.\n",
            "  ConvergenceWarning)\n",
            "/usr/local/lib/python3.6/dist-packages/sklearn/linear_model/_stochastic_gradient.py:1187: ConvergenceWarning: Maximum number of iteration reached before convergence. Consider increasing max_iter to improve the fit.\n",
            "  ConvergenceWarning)\n",
            "/usr/local/lib/python3.6/dist-packages/sklearn/linear_model/_stochastic_gradient.py:1187: ConvergenceWarning: Maximum number of iteration reached before convergence. Consider increasing max_iter to improve the fit.\n",
            "  ConvergenceWarning)\n",
            "/usr/local/lib/python3.6/dist-packages/sklearn/linear_model/_stochastic_gradient.py:1187: ConvergenceWarning: Maximum number of iteration reached before convergence. Consider increasing max_iter to improve the fit.\n",
            "  ConvergenceWarning)\n",
            "/usr/local/lib/python3.6/dist-packages/sklearn/linear_model/_stochastic_gradient.py:1187: ConvergenceWarning: Maximum number of iteration reached before convergence. Consider increasing max_iter to improve the fit.\n",
            "  ConvergenceWarning)\n",
            "/usr/local/lib/python3.6/dist-packages/sklearn/linear_model/_stochastic_gradient.py:1187: ConvergenceWarning: Maximum number of iteration reached before convergence. Consider increasing max_iter to improve the fit.\n",
            "  ConvergenceWarning)\n",
            "/usr/local/lib/python3.6/dist-packages/sklearn/linear_model/_stochastic_gradient.py:1187: ConvergenceWarning: Maximum number of iteration reached before convergence. Consider increasing max_iter to improve the fit.\n",
            "  ConvergenceWarning)\n",
            "/usr/local/lib/python3.6/dist-packages/sklearn/linear_model/_stochastic_gradient.py:1187: ConvergenceWarning: Maximum number of iteration reached before convergence. Consider increasing max_iter to improve the fit.\n",
            "  ConvergenceWarning)\n",
            "/usr/local/lib/python3.6/dist-packages/sklearn/linear_model/_stochastic_gradient.py:1187: ConvergenceWarning: Maximum number of iteration reached before convergence. Consider increasing max_iter to improve the fit.\n",
            "  ConvergenceWarning)\n",
            "/usr/local/lib/python3.6/dist-packages/sklearn/linear_model/_stochastic_gradient.py:1187: ConvergenceWarning: Maximum number of iteration reached before convergence. Consider increasing max_iter to improve the fit.\n",
            "  ConvergenceWarning)\n",
            "/usr/local/lib/python3.6/dist-packages/sklearn/linear_model/_stochastic_gradient.py:1187: ConvergenceWarning: Maximum number of iteration reached before convergence. Consider increasing max_iter to improve the fit.\n",
            "  ConvergenceWarning)\n",
            "/usr/local/lib/python3.6/dist-packages/sklearn/linear_model/_stochastic_gradient.py:1187: ConvergenceWarning: Maximum number of iteration reached before convergence. Consider increasing max_iter to improve the fit.\n",
            "  ConvergenceWarning)\n",
            "/usr/local/lib/python3.6/dist-packages/sklearn/linear_model/_stochastic_gradient.py:1187: ConvergenceWarning: Maximum number of iteration reached before convergence. Consider increasing max_iter to improve the fit.\n",
            "  ConvergenceWarning)\n",
            "/usr/local/lib/python3.6/dist-packages/sklearn/linear_model/_stochastic_gradient.py:1187: ConvergenceWarning: Maximum number of iteration reached before convergence. Consider increasing max_iter to improve the fit.\n",
            "  ConvergenceWarning)\n",
            "/usr/local/lib/python3.6/dist-packages/sklearn/linear_model/_stochastic_gradient.py:1187: ConvergenceWarning: Maximum number of iteration reached before convergence. Consider increasing max_iter to improve the fit.\n",
            "  ConvergenceWarning)\n",
            "/usr/local/lib/python3.6/dist-packages/sklearn/linear_model/_stochastic_gradient.py:1187: ConvergenceWarning: Maximum number of iteration reached before convergence. Consider increasing max_iter to improve the fit.\n",
            "  ConvergenceWarning)\n",
            "/usr/local/lib/python3.6/dist-packages/sklearn/linear_model/_stochastic_gradient.py:1187: ConvergenceWarning: Maximum number of iteration reached before convergence. Consider increasing max_iter to improve the fit.\n",
            "  ConvergenceWarning)\n",
            "/usr/local/lib/python3.6/dist-packages/sklearn/linear_model/_stochastic_gradient.py:1187: ConvergenceWarning: Maximum number of iteration reached before convergence. Consider increasing max_iter to improve the fit.\n",
            "  ConvergenceWarning)\n",
            "/usr/local/lib/python3.6/dist-packages/sklearn/linear_model/_stochastic_gradient.py:1187: ConvergenceWarning: Maximum number of iteration reached before convergence. Consider increasing max_iter to improve the fit.\n",
            "  ConvergenceWarning)\n",
            "/usr/local/lib/python3.6/dist-packages/sklearn/linear_model/_stochastic_gradient.py:1187: ConvergenceWarning: Maximum number of iteration reached before convergence. Consider increasing max_iter to improve the fit.\n",
            "  ConvergenceWarning)\n",
            "/usr/local/lib/python3.6/dist-packages/sklearn/linear_model/_stochastic_gradient.py:1187: ConvergenceWarning: Maximum number of iteration reached before convergence. Consider increasing max_iter to improve the fit.\n",
            "  ConvergenceWarning)\n",
            "/usr/local/lib/python3.6/dist-packages/sklearn/linear_model/_stochastic_gradient.py:1187: ConvergenceWarning: Maximum number of iteration reached before convergence. Consider increasing max_iter to improve the fit.\n",
            "  ConvergenceWarning)\n",
            "/usr/local/lib/python3.6/dist-packages/sklearn/linear_model/_stochastic_gradient.py:1187: ConvergenceWarning: Maximum number of iteration reached before convergence. Consider increasing max_iter to improve the fit.\n",
            "  ConvergenceWarning)\n",
            "/usr/local/lib/python3.6/dist-packages/sklearn/linear_model/_stochastic_gradient.py:1187: ConvergenceWarning: Maximum number of iteration reached before convergence. Consider increasing max_iter to improve the fit.\n",
            "  ConvergenceWarning)\n",
            "/usr/local/lib/python3.6/dist-packages/sklearn/linear_model/_stochastic_gradient.py:1187: ConvergenceWarning: Maximum number of iteration reached before convergence. Consider increasing max_iter to improve the fit.\n",
            "  ConvergenceWarning)\n",
            "/usr/local/lib/python3.6/dist-packages/sklearn/linear_model/_stochastic_gradient.py:1187: ConvergenceWarning: Maximum number of iteration reached before convergence. Consider increasing max_iter to improve the fit.\n",
            "  ConvergenceWarning)\n",
            "/usr/local/lib/python3.6/dist-packages/sklearn/linear_model/_stochastic_gradient.py:1187: ConvergenceWarning: Maximum number of iteration reached before convergence. Consider increasing max_iter to improve the fit.\n",
            "  ConvergenceWarning)\n",
            "/usr/local/lib/python3.6/dist-packages/sklearn/linear_model/_stochastic_gradient.py:1187: ConvergenceWarning: Maximum number of iteration reached before convergence. Consider increasing max_iter to improve the fit.\n",
            "  ConvergenceWarning)\n",
            "/usr/local/lib/python3.6/dist-packages/sklearn/linear_model/_stochastic_gradient.py:1187: ConvergenceWarning: Maximum number of iteration reached before convergence. Consider increasing max_iter to improve the fit.\n",
            "  ConvergenceWarning)\n",
            "/usr/local/lib/python3.6/dist-packages/sklearn/linear_model/_stochastic_gradient.py:1187: ConvergenceWarning: Maximum number of iteration reached before convergence. Consider increasing max_iter to improve the fit.\n",
            "  ConvergenceWarning)\n",
            "/usr/local/lib/python3.6/dist-packages/sklearn/linear_model/_stochastic_gradient.py:1187: ConvergenceWarning: Maximum number of iteration reached before convergence. Consider increasing max_iter to improve the fit.\n",
            "  ConvergenceWarning)\n",
            "/usr/local/lib/python3.6/dist-packages/sklearn/linear_model/_stochastic_gradient.py:1187: ConvergenceWarning: Maximum number of iteration reached before convergence. Consider increasing max_iter to improve the fit.\n",
            "  ConvergenceWarning)\n",
            "/usr/local/lib/python3.6/dist-packages/sklearn/linear_model/_stochastic_gradient.py:1187: ConvergenceWarning: Maximum number of iteration reached before convergence. Consider increasing max_iter to improve the fit.\n",
            "  ConvergenceWarning)\n",
            "/usr/local/lib/python3.6/dist-packages/sklearn/linear_model/_stochastic_gradient.py:1187: ConvergenceWarning: Maximum number of iteration reached before convergence. Consider increasing max_iter to improve the fit.\n",
            "  ConvergenceWarning)\n",
            "/usr/local/lib/python3.6/dist-packages/sklearn/linear_model/_stochastic_gradient.py:1187: ConvergenceWarning: Maximum number of iteration reached before convergence. Consider increasing max_iter to improve the fit.\n",
            "  ConvergenceWarning)\n",
            "/usr/local/lib/python3.6/dist-packages/sklearn/linear_model/_stochastic_gradient.py:1187: ConvergenceWarning: Maximum number of iteration reached before convergence. Consider increasing max_iter to improve the fit.\n",
            "  ConvergenceWarning)\n",
            "/usr/local/lib/python3.6/dist-packages/sklearn/linear_model/_stochastic_gradient.py:1187: ConvergenceWarning: Maximum number of iteration reached before convergence. Consider increasing max_iter to improve the fit.\n",
            "  ConvergenceWarning)\n",
            "/usr/local/lib/python3.6/dist-packages/sklearn/linear_model/_stochastic_gradient.py:1187: ConvergenceWarning: Maximum number of iteration reached before convergence. Consider increasing max_iter to improve the fit.\n",
            "  ConvergenceWarning)\n",
            "/usr/local/lib/python3.6/dist-packages/sklearn/linear_model/_stochastic_gradient.py:1187: ConvergenceWarning: Maximum number of iteration reached before convergence. Consider increasing max_iter to improve the fit.\n",
            "  ConvergenceWarning)\n",
            "/usr/local/lib/python3.6/dist-packages/sklearn/linear_model/_stochastic_gradient.py:1187: ConvergenceWarning: Maximum number of iteration reached before convergence. Consider increasing max_iter to improve the fit.\n",
            "  ConvergenceWarning)\n",
            "/usr/local/lib/python3.6/dist-packages/sklearn/linear_model/_stochastic_gradient.py:1187: ConvergenceWarning: Maximum number of iteration reached before convergence. Consider increasing max_iter to improve the fit.\n",
            "  ConvergenceWarning)\n",
            "/usr/local/lib/python3.6/dist-packages/sklearn/linear_model/_stochastic_gradient.py:1187: ConvergenceWarning: Maximum number of iteration reached before convergence. Consider increasing max_iter to improve the fit.\n",
            "  ConvergenceWarning)\n",
            "/usr/local/lib/python3.6/dist-packages/sklearn/linear_model/_stochastic_gradient.py:1187: ConvergenceWarning: Maximum number of iteration reached before convergence. Consider increasing max_iter to improve the fit.\n",
            "  ConvergenceWarning)\n",
            "/usr/local/lib/python3.6/dist-packages/sklearn/linear_model/_stochastic_gradient.py:1187: ConvergenceWarning: Maximum number of iteration reached before convergence. Consider increasing max_iter to improve the fit.\n",
            "  ConvergenceWarning)\n",
            "/usr/local/lib/python3.6/dist-packages/sklearn/linear_model/_stochastic_gradient.py:1187: ConvergenceWarning: Maximum number of iteration reached before convergence. Consider increasing max_iter to improve the fit.\n",
            "  ConvergenceWarning)\n",
            "/usr/local/lib/python3.6/dist-packages/sklearn/linear_model/_stochastic_gradient.py:1187: ConvergenceWarning: Maximum number of iteration reached before convergence. Consider increasing max_iter to improve the fit.\n",
            "  ConvergenceWarning)\n",
            "/usr/local/lib/python3.6/dist-packages/sklearn/linear_model/_stochastic_gradient.py:1187: ConvergenceWarning: Maximum number of iteration reached before convergence. Consider increasing max_iter to improve the fit.\n",
            "  ConvergenceWarning)\n",
            "/usr/local/lib/python3.6/dist-packages/sklearn/linear_model/_stochastic_gradient.py:1187: ConvergenceWarning: Maximum number of iteration reached before convergence. Consider increasing max_iter to improve the fit.\n",
            "  ConvergenceWarning)\n",
            "/usr/local/lib/python3.6/dist-packages/sklearn/linear_model/_stochastic_gradient.py:1187: ConvergenceWarning: Maximum number of iteration reached before convergence. Consider increasing max_iter to improve the fit.\n",
            "  ConvergenceWarning)\n",
            "/usr/local/lib/python3.6/dist-packages/sklearn/linear_model/_stochastic_gradient.py:1187: ConvergenceWarning: Maximum number of iteration reached before convergence. Consider increasing max_iter to improve the fit.\n",
            "  ConvergenceWarning)\n",
            "/usr/local/lib/python3.6/dist-packages/sklearn/linear_model/_stochastic_gradient.py:1187: ConvergenceWarning: Maximum number of iteration reached before convergence. Consider increasing max_iter to improve the fit.\n",
            "  ConvergenceWarning)\n",
            "/usr/local/lib/python3.6/dist-packages/sklearn/linear_model/_stochastic_gradient.py:1187: ConvergenceWarning: Maximum number of iteration reached before convergence. Consider increasing max_iter to improve the fit.\n",
            "  ConvergenceWarning)\n",
            "/usr/local/lib/python3.6/dist-packages/sklearn/linear_model/_stochastic_gradient.py:1187: ConvergenceWarning: Maximum number of iteration reached before convergence. Consider increasing max_iter to improve the fit.\n",
            "  ConvergenceWarning)\n",
            "/usr/local/lib/python3.6/dist-packages/sklearn/linear_model/_stochastic_gradient.py:1187: ConvergenceWarning: Maximum number of iteration reached before convergence. Consider increasing max_iter to improve the fit.\n",
            "  ConvergenceWarning)\n",
            "/usr/local/lib/python3.6/dist-packages/sklearn/linear_model/_stochastic_gradient.py:1187: ConvergenceWarning: Maximum number of iteration reached before convergence. Consider increasing max_iter to improve the fit.\n",
            "  ConvergenceWarning)\n",
            "/usr/local/lib/python3.6/dist-packages/sklearn/linear_model/_stochastic_gradient.py:1187: ConvergenceWarning: Maximum number of iteration reached before convergence. Consider increasing max_iter to improve the fit.\n",
            "  ConvergenceWarning)\n",
            "/usr/local/lib/python3.6/dist-packages/sklearn/linear_model/_stochastic_gradient.py:1187: ConvergenceWarning: Maximum number of iteration reached before convergence. Consider increasing max_iter to improve the fit.\n",
            "  ConvergenceWarning)\n",
            "/usr/local/lib/python3.6/dist-packages/sklearn/linear_model/_stochastic_gradient.py:1187: ConvergenceWarning: Maximum number of iteration reached before convergence. Consider increasing max_iter to improve the fit.\n",
            "  ConvergenceWarning)\n",
            "/usr/local/lib/python3.6/dist-packages/sklearn/linear_model/_stochastic_gradient.py:1187: ConvergenceWarning: Maximum number of iteration reached before convergence. Consider increasing max_iter to improve the fit.\n",
            "  ConvergenceWarning)\n",
            "/usr/local/lib/python3.6/dist-packages/sklearn/linear_model/_stochastic_gradient.py:1187: ConvergenceWarning: Maximum number of iteration reached before convergence. Consider increasing max_iter to improve the fit.\n",
            "  ConvergenceWarning)\n",
            "/usr/local/lib/python3.6/dist-packages/sklearn/linear_model/_stochastic_gradient.py:1187: ConvergenceWarning: Maximum number of iteration reached before convergence. Consider increasing max_iter to improve the fit.\n",
            "  ConvergenceWarning)\n",
            "/usr/local/lib/python3.6/dist-packages/sklearn/linear_model/_stochastic_gradient.py:1187: ConvergenceWarning: Maximum number of iteration reached before convergence. Consider increasing max_iter to improve the fit.\n",
            "  ConvergenceWarning)\n",
            "/usr/local/lib/python3.6/dist-packages/sklearn/linear_model/_stochastic_gradient.py:1187: ConvergenceWarning: Maximum number of iteration reached before convergence. Consider increasing max_iter to improve the fit.\n",
            "  ConvergenceWarning)\n",
            "/usr/local/lib/python3.6/dist-packages/sklearn/linear_model/_stochastic_gradient.py:1187: ConvergenceWarning: Maximum number of iteration reached before convergence. Consider increasing max_iter to improve the fit.\n",
            "  ConvergenceWarning)\n",
            "/usr/local/lib/python3.6/dist-packages/sklearn/linear_model/_stochastic_gradient.py:1187: ConvergenceWarning: Maximum number of iteration reached before convergence. Consider increasing max_iter to improve the fit.\n",
            "  ConvergenceWarning)\n",
            "/usr/local/lib/python3.6/dist-packages/sklearn/linear_model/_stochastic_gradient.py:1187: ConvergenceWarning: Maximum number of iteration reached before convergence. Consider increasing max_iter to improve the fit.\n",
            "  ConvergenceWarning)\n",
            "/usr/local/lib/python3.6/dist-packages/sklearn/linear_model/_stochastic_gradient.py:1187: ConvergenceWarning: Maximum number of iteration reached before convergence. Consider increasing max_iter to improve the fit.\n",
            "  ConvergenceWarning)\n",
            "/usr/local/lib/python3.6/dist-packages/sklearn/linear_model/_stochastic_gradient.py:1187: ConvergenceWarning: Maximum number of iteration reached before convergence. Consider increasing max_iter to improve the fit.\n",
            "  ConvergenceWarning)\n",
            "/usr/local/lib/python3.6/dist-packages/sklearn/linear_model/_stochastic_gradient.py:1187: ConvergenceWarning: Maximum number of iteration reached before convergence. Consider increasing max_iter to improve the fit.\n",
            "  ConvergenceWarning)\n",
            "/usr/local/lib/python3.6/dist-packages/sklearn/linear_model/_stochastic_gradient.py:1187: ConvergenceWarning: Maximum number of iteration reached before convergence. Consider increasing max_iter to improve the fit.\n",
            "  ConvergenceWarning)\n",
            "/usr/local/lib/python3.6/dist-packages/sklearn/linear_model/_stochastic_gradient.py:1187: ConvergenceWarning: Maximum number of iteration reached before convergence. Consider increasing max_iter to improve the fit.\n",
            "  ConvergenceWarning)\n",
            "/usr/local/lib/python3.6/dist-packages/sklearn/linear_model/_stochastic_gradient.py:1187: ConvergenceWarning: Maximum number of iteration reached before convergence. Consider increasing max_iter to improve the fit.\n",
            "  ConvergenceWarning)\n",
            "/usr/local/lib/python3.6/dist-packages/sklearn/linear_model/_stochastic_gradient.py:1187: ConvergenceWarning: Maximum number of iteration reached before convergence. Consider increasing max_iter to improve the fit.\n",
            "  ConvergenceWarning)\n",
            "/usr/local/lib/python3.6/dist-packages/sklearn/linear_model/_stochastic_gradient.py:1187: ConvergenceWarning: Maximum number of iteration reached before convergence. Consider increasing max_iter to improve the fit.\n",
            "  ConvergenceWarning)\n",
            "/usr/local/lib/python3.6/dist-packages/sklearn/linear_model/_stochastic_gradient.py:1187: ConvergenceWarning: Maximum number of iteration reached before convergence. Consider increasing max_iter to improve the fit.\n",
            "  ConvergenceWarning)\n",
            "/usr/local/lib/python3.6/dist-packages/sklearn/linear_model/_stochastic_gradient.py:1187: ConvergenceWarning: Maximum number of iteration reached before convergence. Consider increasing max_iter to improve the fit.\n",
            "  ConvergenceWarning)\n",
            "/usr/local/lib/python3.6/dist-packages/sklearn/linear_model/_stochastic_gradient.py:1187: ConvergenceWarning: Maximum number of iteration reached before convergence. Consider increasing max_iter to improve the fit.\n",
            "  ConvergenceWarning)\n",
            "/usr/local/lib/python3.6/dist-packages/sklearn/linear_model/_stochastic_gradient.py:1187: ConvergenceWarning: Maximum number of iteration reached before convergence. Consider increasing max_iter to improve the fit.\n",
            "  ConvergenceWarning)\n",
            "/usr/local/lib/python3.6/dist-packages/sklearn/linear_model/_stochastic_gradient.py:1187: ConvergenceWarning: Maximum number of iteration reached before convergence. Consider increasing max_iter to improve the fit.\n",
            "  ConvergenceWarning)\n",
            "/usr/local/lib/python3.6/dist-packages/sklearn/linear_model/_stochastic_gradient.py:1187: ConvergenceWarning: Maximum number of iteration reached before convergence. Consider increasing max_iter to improve the fit.\n",
            "  ConvergenceWarning)\n",
            "/usr/local/lib/python3.6/dist-packages/sklearn/linear_model/_stochastic_gradient.py:1187: ConvergenceWarning: Maximum number of iteration reached before convergence. Consider increasing max_iter to improve the fit.\n",
            "  ConvergenceWarning)\n",
            "/usr/local/lib/python3.6/dist-packages/sklearn/linear_model/_stochastic_gradient.py:1187: ConvergenceWarning: Maximum number of iteration reached before convergence. Consider increasing max_iter to improve the fit.\n",
            "  ConvergenceWarning)\n",
            "/usr/local/lib/python3.6/dist-packages/sklearn/linear_model/_stochastic_gradient.py:1187: ConvergenceWarning: Maximum number of iteration reached before convergence. Consider increasing max_iter to improve the fit.\n",
            "  ConvergenceWarning)\n",
            "/usr/local/lib/python3.6/dist-packages/sklearn/linear_model/_stochastic_gradient.py:1187: ConvergenceWarning: Maximum number of iteration reached before convergence. Consider increasing max_iter to improve the fit.\n",
            "  ConvergenceWarning)\n",
            "/usr/local/lib/python3.6/dist-packages/sklearn/linear_model/_stochastic_gradient.py:1187: ConvergenceWarning: Maximum number of iteration reached before convergence. Consider increasing max_iter to improve the fit.\n",
            "  ConvergenceWarning)\n",
            "/usr/local/lib/python3.6/dist-packages/sklearn/linear_model/_stochastic_gradient.py:1187: ConvergenceWarning: Maximum number of iteration reached before convergence. Consider increasing max_iter to improve the fit.\n",
            "  ConvergenceWarning)\n",
            "/usr/local/lib/python3.6/dist-packages/sklearn/linear_model/_stochastic_gradient.py:1187: ConvergenceWarning: Maximum number of iteration reached before convergence. Consider increasing max_iter to improve the fit.\n",
            "  ConvergenceWarning)\n",
            "/usr/local/lib/python3.6/dist-packages/sklearn/linear_model/_stochastic_gradient.py:1187: ConvergenceWarning: Maximum number of iteration reached before convergence. Consider increasing max_iter to improve the fit.\n",
            "  ConvergenceWarning)\n",
            "/usr/local/lib/python3.6/dist-packages/sklearn/linear_model/_stochastic_gradient.py:1187: ConvergenceWarning: Maximum number of iteration reached before convergence. Consider increasing max_iter to improve the fit.\n",
            "  ConvergenceWarning)\n",
            "/usr/local/lib/python3.6/dist-packages/sklearn/linear_model/_stochastic_gradient.py:1187: ConvergenceWarning: Maximum number of iteration reached before convergence. Consider increasing max_iter to improve the fit.\n",
            "  ConvergenceWarning)\n",
            "/usr/local/lib/python3.6/dist-packages/sklearn/linear_model/_stochastic_gradient.py:1187: ConvergenceWarning: Maximum number of iteration reached before convergence. Consider increasing max_iter to improve the fit.\n",
            "  ConvergenceWarning)\n",
            "/usr/local/lib/python3.6/dist-packages/sklearn/linear_model/_stochastic_gradient.py:1187: ConvergenceWarning: Maximum number of iteration reached before convergence. Consider increasing max_iter to improve the fit.\n",
            "  ConvergenceWarning)\n",
            "/usr/local/lib/python3.6/dist-packages/sklearn/linear_model/_stochastic_gradient.py:1187: ConvergenceWarning: Maximum number of iteration reached before convergence. Consider increasing max_iter to improve the fit.\n",
            "  ConvergenceWarning)\n",
            "/usr/local/lib/python3.6/dist-packages/sklearn/linear_model/_stochastic_gradient.py:1187: ConvergenceWarning: Maximum number of iteration reached before convergence. Consider increasing max_iter to improve the fit.\n",
            "  ConvergenceWarning)\n",
            "/usr/local/lib/python3.6/dist-packages/sklearn/linear_model/_stochastic_gradient.py:1187: ConvergenceWarning: Maximum number of iteration reached before convergence. Consider increasing max_iter to improve the fit.\n",
            "  ConvergenceWarning)\n",
            "/usr/local/lib/python3.6/dist-packages/sklearn/linear_model/_stochastic_gradient.py:1187: ConvergenceWarning: Maximum number of iteration reached before convergence. Consider increasing max_iter to improve the fit.\n",
            "  ConvergenceWarning)\n",
            "/usr/local/lib/python3.6/dist-packages/sklearn/linear_model/_stochastic_gradient.py:1187: ConvergenceWarning: Maximum number of iteration reached before convergence. Consider increasing max_iter to improve the fit.\n",
            "  ConvergenceWarning)\n",
            "/usr/local/lib/python3.6/dist-packages/sklearn/linear_model/_stochastic_gradient.py:1187: ConvergenceWarning: Maximum number of iteration reached before convergence. Consider increasing max_iter to improve the fit.\n",
            "  ConvergenceWarning)\n",
            "/usr/local/lib/python3.6/dist-packages/sklearn/linear_model/_stochastic_gradient.py:1187: ConvergenceWarning: Maximum number of iteration reached before convergence. Consider increasing max_iter to improve the fit.\n",
            "  ConvergenceWarning)\n",
            "/usr/local/lib/python3.6/dist-packages/sklearn/linear_model/_stochastic_gradient.py:1187: ConvergenceWarning: Maximum number of iteration reached before convergence. Consider increasing max_iter to improve the fit.\n",
            "  ConvergenceWarning)\n",
            "/usr/local/lib/python3.6/dist-packages/sklearn/linear_model/_stochastic_gradient.py:1187: ConvergenceWarning: Maximum number of iteration reached before convergence. Consider increasing max_iter to improve the fit.\n",
            "  ConvergenceWarning)\n",
            "/usr/local/lib/python3.6/dist-packages/sklearn/linear_model/_stochastic_gradient.py:1187: ConvergenceWarning: Maximum number of iteration reached before convergence. Consider increasing max_iter to improve the fit.\n",
            "  ConvergenceWarning)\n",
            "/usr/local/lib/python3.6/dist-packages/sklearn/linear_model/_stochastic_gradient.py:1187: ConvergenceWarning: Maximum number of iteration reached before convergence. Consider increasing max_iter to improve the fit.\n",
            "  ConvergenceWarning)\n",
            "/usr/local/lib/python3.6/dist-packages/sklearn/linear_model/_stochastic_gradient.py:1187: ConvergenceWarning: Maximum number of iteration reached before convergence. Consider increasing max_iter to improve the fit.\n",
            "  ConvergenceWarning)\n",
            "/usr/local/lib/python3.6/dist-packages/sklearn/linear_model/_stochastic_gradient.py:1187: ConvergenceWarning: Maximum number of iteration reached before convergence. Consider increasing max_iter to improve the fit.\n",
            "  ConvergenceWarning)\n",
            "/usr/local/lib/python3.6/dist-packages/sklearn/linear_model/_stochastic_gradient.py:1187: ConvergenceWarning: Maximum number of iteration reached before convergence. Consider increasing max_iter to improve the fit.\n",
            "  ConvergenceWarning)\n",
            "/usr/local/lib/python3.6/dist-packages/sklearn/linear_model/_stochastic_gradient.py:1187: ConvergenceWarning: Maximum number of iteration reached before convergence. Consider increasing max_iter to improve the fit.\n",
            "  ConvergenceWarning)\n",
            "/usr/local/lib/python3.6/dist-packages/sklearn/linear_model/_stochastic_gradient.py:1187: ConvergenceWarning: Maximum number of iteration reached before convergence. Consider increasing max_iter to improve the fit.\n",
            "  ConvergenceWarning)\n",
            "/usr/local/lib/python3.6/dist-packages/sklearn/linear_model/_stochastic_gradient.py:1187: ConvergenceWarning: Maximum number of iteration reached before convergence. Consider increasing max_iter to improve the fit.\n",
            "  ConvergenceWarning)\n",
            "/usr/local/lib/python3.6/dist-packages/sklearn/linear_model/_stochastic_gradient.py:1187: ConvergenceWarning: Maximum number of iteration reached before convergence. Consider increasing max_iter to improve the fit.\n",
            "  ConvergenceWarning)\n",
            "/usr/local/lib/python3.6/dist-packages/sklearn/linear_model/_stochastic_gradient.py:1187: ConvergenceWarning: Maximum number of iteration reached before convergence. Consider increasing max_iter to improve the fit.\n",
            "  ConvergenceWarning)\n",
            "/usr/local/lib/python3.6/dist-packages/sklearn/linear_model/_stochastic_gradient.py:1187: ConvergenceWarning: Maximum number of iteration reached before convergence. Consider increasing max_iter to improve the fit.\n",
            "  ConvergenceWarning)\n",
            "/usr/local/lib/python3.6/dist-packages/sklearn/linear_model/_stochastic_gradient.py:1187: ConvergenceWarning: Maximum number of iteration reached before convergence. Consider increasing max_iter to improve the fit.\n",
            "  ConvergenceWarning)\n",
            "/usr/local/lib/python3.6/dist-packages/sklearn/linear_model/_stochastic_gradient.py:1187: ConvergenceWarning: Maximum number of iteration reached before convergence. Consider increasing max_iter to improve the fit.\n",
            "  ConvergenceWarning)\n",
            "/usr/local/lib/python3.6/dist-packages/sklearn/linear_model/_stochastic_gradient.py:1187: ConvergenceWarning: Maximum number of iteration reached before convergence. Consider increasing max_iter to improve the fit.\n",
            "  ConvergenceWarning)\n",
            "/usr/local/lib/python3.6/dist-packages/sklearn/linear_model/_stochastic_gradient.py:1187: ConvergenceWarning: Maximum number of iteration reached before convergence. Consider increasing max_iter to improve the fit.\n",
            "  ConvergenceWarning)\n",
            "/usr/local/lib/python3.6/dist-packages/sklearn/linear_model/_stochastic_gradient.py:1187: ConvergenceWarning: Maximum number of iteration reached before convergence. Consider increasing max_iter to improve the fit.\n",
            "  ConvergenceWarning)\n",
            "/usr/local/lib/python3.6/dist-packages/sklearn/linear_model/_stochastic_gradient.py:1187: ConvergenceWarning: Maximum number of iteration reached before convergence. Consider increasing max_iter to improve the fit.\n",
            "  ConvergenceWarning)\n",
            "/usr/local/lib/python3.6/dist-packages/sklearn/linear_model/_stochastic_gradient.py:1187: ConvergenceWarning: Maximum number of iteration reached before convergence. Consider increasing max_iter to improve the fit.\n",
            "  ConvergenceWarning)\n",
            "/usr/local/lib/python3.6/dist-packages/sklearn/linear_model/_stochastic_gradient.py:1187: ConvergenceWarning: Maximum number of iteration reached before convergence. Consider increasing max_iter to improve the fit.\n",
            "  ConvergenceWarning)\n",
            "/usr/local/lib/python3.6/dist-packages/sklearn/linear_model/_stochastic_gradient.py:1187: ConvergenceWarning: Maximum number of iteration reached before convergence. Consider increasing max_iter to improve the fit.\n",
            "  ConvergenceWarning)\n",
            "/usr/local/lib/python3.6/dist-packages/sklearn/linear_model/_stochastic_gradient.py:1187: ConvergenceWarning: Maximum number of iteration reached before convergence. Consider increasing max_iter to improve the fit.\n",
            "  ConvergenceWarning)\n",
            "/usr/local/lib/python3.6/dist-packages/sklearn/linear_model/_stochastic_gradient.py:1187: ConvergenceWarning: Maximum number of iteration reached before convergence. Consider increasing max_iter to improve the fit.\n",
            "  ConvergenceWarning)\n",
            "/usr/local/lib/python3.6/dist-packages/sklearn/linear_model/_stochastic_gradient.py:1187: ConvergenceWarning: Maximum number of iteration reached before convergence. Consider increasing max_iter to improve the fit.\n",
            "  ConvergenceWarning)\n",
            "/usr/local/lib/python3.6/dist-packages/sklearn/linear_model/_stochastic_gradient.py:1187: ConvergenceWarning: Maximum number of iteration reached before convergence. Consider increasing max_iter to improve the fit.\n",
            "  ConvergenceWarning)\n",
            "/usr/local/lib/python3.6/dist-packages/sklearn/linear_model/_stochastic_gradient.py:1187: ConvergenceWarning: Maximum number of iteration reached before convergence. Consider increasing max_iter to improve the fit.\n",
            "  ConvergenceWarning)\n",
            "/usr/local/lib/python3.6/dist-packages/sklearn/linear_model/_stochastic_gradient.py:1187: ConvergenceWarning: Maximum number of iteration reached before convergence. Consider increasing max_iter to improve the fit.\n",
            "  ConvergenceWarning)\n",
            "/usr/local/lib/python3.6/dist-packages/sklearn/linear_model/_stochastic_gradient.py:1187: ConvergenceWarning: Maximum number of iteration reached before convergence. Consider increasing max_iter to improve the fit.\n",
            "  ConvergenceWarning)\n",
            "/usr/local/lib/python3.6/dist-packages/sklearn/linear_model/_stochastic_gradient.py:1187: ConvergenceWarning: Maximum number of iteration reached before convergence. Consider increasing max_iter to improve the fit.\n",
            "  ConvergenceWarning)\n",
            "/usr/local/lib/python3.6/dist-packages/sklearn/linear_model/_stochastic_gradient.py:1187: ConvergenceWarning: Maximum number of iteration reached before convergence. Consider increasing max_iter to improve the fit.\n",
            "  ConvergenceWarning)\n",
            "/usr/local/lib/python3.6/dist-packages/sklearn/linear_model/_stochastic_gradient.py:1187: ConvergenceWarning: Maximum number of iteration reached before convergence. Consider increasing max_iter to improve the fit.\n",
            "  ConvergenceWarning)\n",
            "/usr/local/lib/python3.6/dist-packages/sklearn/linear_model/_stochastic_gradient.py:1187: ConvergenceWarning: Maximum number of iteration reached before convergence. Consider increasing max_iter to improve the fit.\n",
            "  ConvergenceWarning)\n",
            "/usr/local/lib/python3.6/dist-packages/sklearn/linear_model/_stochastic_gradient.py:1187: ConvergenceWarning: Maximum number of iteration reached before convergence. Consider increasing max_iter to improve the fit.\n",
            "  ConvergenceWarning)\n",
            "/usr/local/lib/python3.6/dist-packages/sklearn/linear_model/_stochastic_gradient.py:1187: ConvergenceWarning: Maximum number of iteration reached before convergence. Consider increasing max_iter to improve the fit.\n",
            "  ConvergenceWarning)\n",
            "/usr/local/lib/python3.6/dist-packages/sklearn/linear_model/_stochastic_gradient.py:1187: ConvergenceWarning: Maximum number of iteration reached before convergence. Consider increasing max_iter to improve the fit.\n",
            "  ConvergenceWarning)\n",
            "/usr/local/lib/python3.6/dist-packages/sklearn/linear_model/_stochastic_gradient.py:1187: ConvergenceWarning: Maximum number of iteration reached before convergence. Consider increasing max_iter to improve the fit.\n",
            "  ConvergenceWarning)\n",
            "/usr/local/lib/python3.6/dist-packages/sklearn/linear_model/_stochastic_gradient.py:1187: ConvergenceWarning: Maximum number of iteration reached before convergence. Consider increasing max_iter to improve the fit.\n",
            "  ConvergenceWarning)\n",
            "/usr/local/lib/python3.6/dist-packages/sklearn/linear_model/_stochastic_gradient.py:1187: ConvergenceWarning: Maximum number of iteration reached before convergence. Consider increasing max_iter to improve the fit.\n",
            "  ConvergenceWarning)\n",
            "/usr/local/lib/python3.6/dist-packages/sklearn/linear_model/_stochastic_gradient.py:1187: ConvergenceWarning: Maximum number of iteration reached before convergence. Consider increasing max_iter to improve the fit.\n",
            "  ConvergenceWarning)\n",
            "/usr/local/lib/python3.6/dist-packages/sklearn/linear_model/_stochastic_gradient.py:1187: ConvergenceWarning: Maximum number of iteration reached before convergence. Consider increasing max_iter to improve the fit.\n",
            "  ConvergenceWarning)\n",
            "/usr/local/lib/python3.6/dist-packages/sklearn/linear_model/_stochastic_gradient.py:1187: ConvergenceWarning: Maximum number of iteration reached before convergence. Consider increasing max_iter to improve the fit.\n",
            "  ConvergenceWarning)\n",
            "/usr/local/lib/python3.6/dist-packages/sklearn/linear_model/_stochastic_gradient.py:1187: ConvergenceWarning: Maximum number of iteration reached before convergence. Consider increasing max_iter to improve the fit.\n",
            "  ConvergenceWarning)\n",
            "/usr/local/lib/python3.6/dist-packages/sklearn/linear_model/_stochastic_gradient.py:1187: ConvergenceWarning: Maximum number of iteration reached before convergence. Consider increasing max_iter to improve the fit.\n",
            "  ConvergenceWarning)\n",
            "/usr/local/lib/python3.6/dist-packages/sklearn/linear_model/_stochastic_gradient.py:1187: ConvergenceWarning: Maximum number of iteration reached before convergence. Consider increasing max_iter to improve the fit.\n",
            "  ConvergenceWarning)\n",
            "/usr/local/lib/python3.6/dist-packages/sklearn/linear_model/_stochastic_gradient.py:1187: ConvergenceWarning: Maximum number of iteration reached before convergence. Consider increasing max_iter to improve the fit.\n",
            "  ConvergenceWarning)\n",
            "/usr/local/lib/python3.6/dist-packages/sklearn/linear_model/_stochastic_gradient.py:1187: ConvergenceWarning: Maximum number of iteration reached before convergence. Consider increasing max_iter to improve the fit.\n",
            "  ConvergenceWarning)\n",
            "/usr/local/lib/python3.6/dist-packages/sklearn/linear_model/_stochastic_gradient.py:1187: ConvergenceWarning: Maximum number of iteration reached before convergence. Consider increasing max_iter to improve the fit.\n",
            "  ConvergenceWarning)\n",
            "/usr/local/lib/python3.6/dist-packages/sklearn/linear_model/_stochastic_gradient.py:1187: ConvergenceWarning: Maximum number of iteration reached before convergence. Consider increasing max_iter to improve the fit.\n",
            "  ConvergenceWarning)\n",
            "/usr/local/lib/python3.6/dist-packages/sklearn/linear_model/_stochastic_gradient.py:1187: ConvergenceWarning: Maximum number of iteration reached before convergence. Consider increasing max_iter to improve the fit.\n",
            "  ConvergenceWarning)\n",
            "/usr/local/lib/python3.6/dist-packages/sklearn/linear_model/_stochastic_gradient.py:1187: ConvergenceWarning: Maximum number of iteration reached before convergence. Consider increasing max_iter to improve the fit.\n",
            "  ConvergenceWarning)\n",
            "/usr/local/lib/python3.6/dist-packages/sklearn/linear_model/_stochastic_gradient.py:1187: ConvergenceWarning: Maximum number of iteration reached before convergence. Consider increasing max_iter to improve the fit.\n",
            "  ConvergenceWarning)\n",
            "/usr/local/lib/python3.6/dist-packages/sklearn/linear_model/_stochastic_gradient.py:1187: ConvergenceWarning: Maximum number of iteration reached before convergence. Consider increasing max_iter to improve the fit.\n",
            "  ConvergenceWarning)\n",
            "/usr/local/lib/python3.6/dist-packages/sklearn/linear_model/_stochastic_gradient.py:1187: ConvergenceWarning: Maximum number of iteration reached before convergence. Consider increasing max_iter to improve the fit.\n",
            "  ConvergenceWarning)\n",
            "/usr/local/lib/python3.6/dist-packages/sklearn/linear_model/_stochastic_gradient.py:1187: ConvergenceWarning: Maximum number of iteration reached before convergence. Consider increasing max_iter to improve the fit.\n",
            "  ConvergenceWarning)\n",
            "/usr/local/lib/python3.6/dist-packages/sklearn/linear_model/_stochastic_gradient.py:1187: ConvergenceWarning: Maximum number of iteration reached before convergence. Consider increasing max_iter to improve the fit.\n",
            "  ConvergenceWarning)\n",
            "/usr/local/lib/python3.6/dist-packages/sklearn/linear_model/_stochastic_gradient.py:1187: ConvergenceWarning: Maximum number of iteration reached before convergence. Consider increasing max_iter to improve the fit.\n",
            "  ConvergenceWarning)\n",
            "/usr/local/lib/python3.6/dist-packages/sklearn/linear_model/_stochastic_gradient.py:1187: ConvergenceWarning: Maximum number of iteration reached before convergence. Consider increasing max_iter to improve the fit.\n",
            "  ConvergenceWarning)\n",
            "/usr/local/lib/python3.6/dist-packages/sklearn/linear_model/_stochastic_gradient.py:1187: ConvergenceWarning: Maximum number of iteration reached before convergence. Consider increasing max_iter to improve the fit.\n",
            "  ConvergenceWarning)\n",
            "/usr/local/lib/python3.6/dist-packages/sklearn/linear_model/_stochastic_gradient.py:1187: ConvergenceWarning: Maximum number of iteration reached before convergence. Consider increasing max_iter to improve the fit.\n",
            "  ConvergenceWarning)\n",
            "/usr/local/lib/python3.6/dist-packages/sklearn/linear_model/_stochastic_gradient.py:1187: ConvergenceWarning: Maximum number of iteration reached before convergence. Consider increasing max_iter to improve the fit.\n",
            "  ConvergenceWarning)\n",
            "/usr/local/lib/python3.6/dist-packages/sklearn/linear_model/_stochastic_gradient.py:1187: ConvergenceWarning: Maximum number of iteration reached before convergence. Consider increasing max_iter to improve the fit.\n",
            "  ConvergenceWarning)\n",
            "/usr/local/lib/python3.6/dist-packages/sklearn/linear_model/_stochastic_gradient.py:1187: ConvergenceWarning: Maximum number of iteration reached before convergence. Consider increasing max_iter to improve the fit.\n",
            "  ConvergenceWarning)\n",
            "/usr/local/lib/python3.6/dist-packages/sklearn/linear_model/_stochastic_gradient.py:1187: ConvergenceWarning: Maximum number of iteration reached before convergence. Consider increasing max_iter to improve the fit.\n",
            "  ConvergenceWarning)\n",
            "/usr/local/lib/python3.6/dist-packages/sklearn/linear_model/_stochastic_gradient.py:1187: ConvergenceWarning: Maximum number of iteration reached before convergence. Consider increasing max_iter to improve the fit.\n",
            "  ConvergenceWarning)\n",
            "/usr/local/lib/python3.6/dist-packages/sklearn/linear_model/_stochastic_gradient.py:1187: ConvergenceWarning: Maximum number of iteration reached before convergence. Consider increasing max_iter to improve the fit.\n",
            "  ConvergenceWarning)\n",
            "/usr/local/lib/python3.6/dist-packages/sklearn/linear_model/_stochastic_gradient.py:1187: ConvergenceWarning: Maximum number of iteration reached before convergence. Consider increasing max_iter to improve the fit.\n",
            "  ConvergenceWarning)\n",
            "/usr/local/lib/python3.6/dist-packages/sklearn/linear_model/_stochastic_gradient.py:1187: ConvergenceWarning: Maximum number of iteration reached before convergence. Consider increasing max_iter to improve the fit.\n",
            "  ConvergenceWarning)\n",
            "/usr/local/lib/python3.6/dist-packages/sklearn/linear_model/_stochastic_gradient.py:1187: ConvergenceWarning: Maximum number of iteration reached before convergence. Consider increasing max_iter to improve the fit.\n",
            "  ConvergenceWarning)\n"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "30.511967490509335\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "VaQPj_aRFEHh",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 36
        },
        "outputId": "713ecf2b-becc-4273-9a97-d7b67e2de946"
      },
      "source": [
        "print(lrate, iterations)"
      ],
      "execution_count": 178,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "5e-07 2500000\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "dG6WuDtjfuFF",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "test_y_hat_sdg = clf2.predict(x_test)\n",
        "val_y_hat_sdg = clf2.predict(x_val)\n",
        "train_y_hat_sdg = clf2.predict(x_train)\n",
        "train_score_sdg = clf2.score(x_train,y_train)\n",
        "test_score_sdg = clf2.score(x_test,y_test)\n",
        "val_score_sdg = clf2.score(x_val,y_val)"
      ],
      "execution_count": 179,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "wQYvfo8gvhNt",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 167
        },
        "outputId": "5bd141d9-aae5-4b0d-d27e-fab88a4be4a5"
      },
      "source": [
        "print(\"R2-score Train: \\t\\t%.2f\" % r2_score(clf2.predict(x_train) , y_train))\n",
        "print(\"R2-score Test: \\t\\t\\t%.2f\" % r2_score(test_y_hat_sdg , y_test))\n",
        "print(\"R2-score Validation: \\t\\t%.2f\" % r2_score(val_y_hat_sdg , y_val))\n",
        "print(\"------------------------------------\")\n",
        "print(\"RMSE test : %.4f\"%math.sqrt(mean_squared_error(y_test,test_y_hat_sdg)))\n",
        "print(\"RMSE train : %.4f\"%math.sqrt(mean_squared_error(y_train,train_y_hat_sdg)))\n",
        "print(\"MAE test : %.4f\"%mean_absolute_error(y_test,test_y_hat_sdg))\n",
        "print(\"MAE train : %.4f\"%mean_absolute_error(y_train,train_y_hat_sdg))"
      ],
      "execution_count": 180,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "R2-score Train: \t\t0.71\n",
            "R2-score Test: \t\t\t0.02\n",
            "R2-score Validation: \t\t0.79\n",
            "------------------------------------\n",
            "RMSE test : 38.9208\n",
            "RMSE train : 41.6753\n",
            "MAE test : 30.5120\n",
            "MAE train : 32.7868\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "lGlLb4-Jbenj",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 284
        },
        "outputId": "29af074f-9dac-4405-e4fe-4b150c9e378a"
      },
      "source": [
        "plt.scatter(y_test,test_y_hat_sdg)"
      ],
      "execution_count": 181,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<matplotlib.collections.PathCollection at 0x7f081a321a20>"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 181
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "k4tYrtYLBspV",
        "colab_type": "text"
      },
      "source": [
        "## 2) Multiple Linear Regression using Gradient Descent\n",
        "### Dataset : Boston Housing DataSet"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "boUVRr-JBwh3",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 206
        },
        "outputId": "c6d7fbec-d879-4f91-b4b7-e3fa9439aed4"
      },
      "source": [
        "from sklearn.datasets import load_boston\n",
        "from sklearn.metrics import mean_squared_error\n",
        "\n",
        "boston_df = pd.DataFrame(load_boston().data,columns = load_boston().feature_names)\n",
        "\n",
        "y = load_boston().target\n",
        "x = load_boston().data\n",
        "\n",
        "boston_df.head(5)"
      ],
      "execution_count": 182,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>CRIM</th>\n",
              "      <th>ZN</th>\n",
              "      <th>INDUS</th>\n",
              "      <th>CHAS</th>\n",
              "      <th>NOX</th>\n",
              "      <th>RM</th>\n",
              "      <th>AGE</th>\n",
              "      <th>DIS</th>\n",
              "      <th>RAD</th>\n",
              "      <th>TAX</th>\n",
              "      <th>PTRATIO</th>\n",
              "      <th>B</th>\n",
              "      <th>LSTAT</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>0.00632</td>\n",
              "      <td>18.0</td>\n",
              "      <td>2.31</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.538</td>\n",
              "      <td>6.575</td>\n",
              "      <td>65.2</td>\n",
              "      <td>4.0900</td>\n",
              "      <td>1.0</td>\n",
              "      <td>296.0</td>\n",
              "      <td>15.3</td>\n",
              "      <td>396.90</td>\n",
              "      <td>4.98</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>0.02731</td>\n",
              "      <td>0.0</td>\n",
              "      <td>7.07</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.469</td>\n",
              "      <td>6.421</td>\n",
              "      <td>78.9</td>\n",
              "      <td>4.9671</td>\n",
              "      <td>2.0</td>\n",
              "      <td>242.0</td>\n",
              "      <td>17.8</td>\n",
              "      <td>396.90</td>\n",
              "      <td>9.14</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>0.02729</td>\n",
              "      <td>0.0</td>\n",
              "      <td>7.07</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.469</td>\n",
              "      <td>7.185</td>\n",
              "      <td>61.1</td>\n",
              "      <td>4.9671</td>\n",
              "      <td>2.0</td>\n",
              "      <td>242.0</td>\n",
              "      <td>17.8</td>\n",
              "      <td>392.83</td>\n",
              "      <td>4.03</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>0.03237</td>\n",
              "      <td>0.0</td>\n",
              "      <td>2.18</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.458</td>\n",
              "      <td>6.998</td>\n",
              "      <td>45.8</td>\n",
              "      <td>6.0622</td>\n",
              "      <td>3.0</td>\n",
              "      <td>222.0</td>\n",
              "      <td>18.7</td>\n",
              "      <td>394.63</td>\n",
              "      <td>2.94</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>0.06905</td>\n",
              "      <td>0.0</td>\n",
              "      <td>2.18</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.458</td>\n",
              "      <td>7.147</td>\n",
              "      <td>54.2</td>\n",
              "      <td>6.0622</td>\n",
              "      <td>3.0</td>\n",
              "      <td>222.0</td>\n",
              "      <td>18.7</td>\n",
              "      <td>396.90</td>\n",
              "      <td>5.33</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "      CRIM    ZN  INDUS  CHAS    NOX  ...  RAD    TAX  PTRATIO       B  LSTAT\n",
              "0  0.00632  18.0   2.31   0.0  0.538  ...  1.0  296.0     15.3  396.90   4.98\n",
              "1  0.02731   0.0   7.07   0.0  0.469  ...  2.0  242.0     17.8  396.90   9.14\n",
              "2  0.02729   0.0   7.07   0.0  0.469  ...  2.0  242.0     17.8  392.83   4.03\n",
              "3  0.03237   0.0   2.18   0.0  0.458  ...  3.0  222.0     18.7  394.63   2.94\n",
              "4  0.06905   0.0   2.18   0.0  0.458  ...  3.0  222.0     18.7  396.90   5.33\n",
              "\n",
              "[5 rows x 13 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 182
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "1z61aIrFF2TW",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 73
        },
        "outputId": "2da35452-1358-4778-81f6-d36164a68bc6"
      },
      "source": [
        "#Train and Test set split into 80% and 20% respectively\n",
        "x_train, x_rest, y_train, y_rest = train_test_split(x,y,test_size = .4,random_state =0)\n",
        "\n",
        "#Rest of the 40% set split into equal parts of Train and Validation set \n",
        "x_test, x_val, y_test, y_val = train_test_split(x_train,y_train,test_size = .5,random_state = 0)\n",
        "\n",
        "#Therefore : Train = 60%, Test = 20% and Validation = 20%\n",
        "print(len(x_train),len(y_train))\n",
        "print(len(x_val),len(y_val))\n",
        "print(len(x_test),len(y_test))"
      ],
      "execution_count": 183,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "303 303\n",
            "152 152\n",
            "151 151\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "6pDeUMg5IeRJ",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "#preprocessing is necessary for SDG Regressor\n",
        "\n",
        "scaler = preprocessing.StandardScaler().fit(x_train)\n",
        "x_train = scaler.transform(x_train)\n",
        "x_test = scaler.transform(x_test)\n",
        "x_val = scaler.transform(x_val)\n",
        "\n",
        "y_train = y_train.reshape(-1)\n",
        "y_test = y_test.reshape(-1)\n",
        "y_val = y_val.reshape(-1)"
      ],
      "execution_count": 184,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "v5OvoSW-LMbx",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "#clf_sdg = SGDRegressor(max_iter= 50000,eta0=0.0001,learning_rate='constant')\n",
        "#learning rate is default = 0.01 as constant = eta0\n",
        "#clf_sdg.fit(x_train,y_train)"
      ],
      "execution_count": 185,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "1cQzza0KGX-6",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "clf2, lrate, lrate_accuracy, iterations = grid_search()"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "fOMTmEaOLhf3",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 36
        },
        "outputId": "3c0248d6-b1ef-45e1-fc18-03b8baab6c6c"
      },
      "source": [
        "print(lrate,iterations)"
      ],
      "execution_count": 190,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "4.9999999999999996e-06 2500000\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "73nFDnmfGTMj",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "y_hat_test = clf_sdg.predict(x_test)\n",
        "y_hat_val = clf_sdg.predict(x_val)\n",
        "y_hat_train = clf_sdg.predict(x_train)\n",
        "\n",
        "test_score = clf_sdg.score(x_test,y_test)\n",
        "train_score = clf_sdg.score(x_train,y_train)\n",
        "val_score = clf_sdg.score(x_val,y_val)"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "57O1QG-JMJgm",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 223
        },
        "outputId": "52893b5a-ed02-4c52-daa8-2668d9e7453d"
      },
      "source": [
        "print(\"R2-score Train: \\t\\t%.2f\" % r2_score(y_hat_train , y_train) )\n",
        "print(\"R2-score Test: \\t\\t\\t%.2f\" % r2_score(y_hat_test , y_test) )\n",
        "print(\"R2-score Validation: \\t\\t%.2f\" % r2_score(y_hat_val , y_val) )\n",
        "print(\"------------------------------------\")\n",
        "print(\"Train score : \\t\\t\\t%.2f\"%train_score)\n",
        "print(\"Test score : \\t\\t\\t%.2f\"%test_score)\n",
        "print(\"Validation Score : \\t\\t%.2f\"%val_score)\n",
        "\n",
        "print(\"Root Mean Squared Error : %3f\"%math.sqrt(mean_squared_error(y_test,y_hat_test)))\n",
        "print(\"MAE train : %3f\"%(mean_absolute_error(y_train,y_hat_train)))\n",
        "print(\"MAE test : %3f\"%(mean_absolute_error(y_test,y_hat_test)))\n",
        "print(\"MAE val : %3f\"%(mean_absolute_error(y_val,y_hat_val)))"
      ],
      "execution_count": 189,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "R2-score Train: \t\t0.68\n",
            "R2-score Test: \t\t\t0.72\n",
            "R2-score Validation: \t\t0.65\n",
            "------------------------------------\n",
            "Train score : \t\t\t0.76\n",
            "Test score : \t\t\t0.77\n",
            "Validation Score : \t\t0.75\n",
            "Root Mean Squared Error : 4.362641\n",
            "MAE train : 3.078017\n",
            "MAE test : 3.073836\n",
            "MAE val : 3.082170\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "FbicltDPxR0q",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 339
        },
        "outputId": "161d5451-877c-421d-abe0-ec754ebd6192"
      },
      "source": [
        "fig,ax = plt.subplots(figsize= (7,5))\n",
        "ax.scatter(y_test,y_hat_test,s=3)"
      ],
      "execution_count": 187,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<matplotlib.collections.PathCollection at 0x7f081b13d240>"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 187
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 504x360 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    }
  ]
}