Machine Learning with Scikit-Learn - The Cancer Dataset - 16 - Random Forests 1.ipynb

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      "Accuracy on the training subset: 1.000\n",
      "Accuracy on the test subset: 0.972\n"
     ]
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   "source": [
    "from sklearn.ensemble import RandomForestClassifier\n",
    "from sklearn.model_selection import train_test_split\n",
    "from sklearn.datasets import load_breast_cancer\n",
    "\n",
    "cancer = load_breast_cancer()\n",
    "\n",
    "X_train, X_test, y_train, y_test = train_test_split(cancer.data, cancer.target, random_state=0)\n",
    "\n",
    "forest = RandomForestClassifier(n_estimators=100, random_state=0)\n",
    "forest.fit(X_train, y_train)\n",
    "\n",
    "print('Accuracy on the training subset: {:.3f}'.format(forest.score(X_train, y_train)))\n",
    "print('Accuracy on the test subset: {:.3f}'.format(forest.score(X_test, y_test)))"
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