I always have this error after executing the following code : NameError: name 'x_train' is not defined

[babesrani]

import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
import seaborn as sns

%matplotlib inline

import os
print(os.listdir())

import warnings
warnings.filterwarnings('ignore')
dataset = pd.read_csv("C:/Users/pavan/OneDrive/Documents/heart (1).csv")
dataset.head(5)
from sklearn.model_selection import train_test_split

predictors = dataset.drop("target",axis=1)
target = dataset["target"]

X_train,X_test,Y_train,Y_test = train_test_split(predictors,target,test_size=0.20,random_state=0)
from sklearn.metrics import accuracy_score from sklearn.ensemble import RandomForestClassifier

max_accuracy = 0

for x in range(2000):
rf = RandomForestClassifier(random_state=x)
rf.fit(X_train,Y_train)
Y_pred_rf = rf.predict(X_test)
current_accuracy = round(accuracy_score(Y_pred_rf,Y_test)*100,2)
if(current_accuracy>max_accuracy):
max_accuracy = current_accuracy
best_x = x

rf = RandomForestClassifier(random_state=best_x)
rf.fit(X_train,Y_train)
Y_pred_rf = rf.predict(X_test)
Y_pred_rf.shape
score_rf = round(accuracy_score(Y_pred_rf,Y_test)*100,2)

print("The accuracy score achieved using Decision Tree is: "+str(score_rf)+" %")

[JonnoFTW]

1: please format your code (paste it inside triple backticks):

 \```
your_code_here() # without the backslash

2: please also include the hyperas code you used to run this.