如何通过测试数据集预测y值？

Question

I have successfully built logistic regression model using train dataset below.

X = train.drop('y', axis=1)
y = train['y']

X_train, X_test, y_train, y_test = train_test_split(X, y, 
                                                    test_size=0.5)

scaler = StandardScaler()  
scaler.fit(X_train)

X_train = scaler.transform(X_train)
X_test = scaler.transform(X_test)

logreg1 = LogisticRegression()
logreg1.fit(X_train, y_train)

score = logreg1.score(X_test, y_test)
cvs = cross_val_score(logreg1, X_test, y_test, cv=5).mean()

My problem is I want to bring in the test dataset to predict the unknown y value. In the test data theres no y column. How can I predict the y value using the seperate test dataset??

Answer 1

Use predict():

y_pred = logreg1.predict(X_test)
score = logreg1.score(X_test, y_pred)
print(y_pred)     // see the predictions