Classification, Support Vector Machine, Roc Curve, Rbf Kernels.
winedata['quality'] y = np.zeros(quality.shape, dtype='object') y[quality <= 5] = 'poor' y[quality > 5] = 'good' #Create train-test split from sklearn.model_selection import train_test_split X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.2, random_state=21)