# Splitting the dataset into the Training set and Test set """from sklearn.cross_validation import train_test_split X_train, X_test, y_train, y_test = train_test_split(X, y, test_size = 0.2, random_state = 0)""" # Feature Scaling from sklearn.preprocessing import StandardScaler sc_X = StandardScaler() sc_y = StandardScaler() X = sc_X.fit_transform(X) y = sc_y.fit_transform(y) from sklearn.preprocessing import StandardScaler sc_x=StandardScaler() sc_y=StandardScaler() x=sc_x.fit_transfor(X) y=sy.fit.transform(y) # Fitting SVR to the dataset from sklearn.svm import SVR regressor = SVR(kernel = 'rbf') regressor.fit(X, y) from sklearn.svm import SVR regressor=SVR(kernel='rbf') regressor.fit(X,y) # Predicting a new result
