z標準化

for feature in X_train.columns.values[:-1]:
    mean, std = data[feature].mean(), data[feature].std()#求出標準差和方差
    X_train.loc[:, feature] = (X_train[feature] - mean) / std
    X_test.loc[:, feature] = (X_test[feature] - mean) / std
    X_validation.loc[:, feature] = (X_validation[feature] - mean) / std
for feature in X_train_.columns.values[:-1]:
    mean, std = data_resampled[feature].mean(), data_resampled[feature].std()
    X_train_.loc[:, feature] = (X_train_[feature] - mean) / std
    X_test_.loc[:, feature] = (X_test_[feature] - mean) / std
    X_validation_.loc[:, feature] = (X_validation_[feature] - mean) / std