Fit logistic regression with L1 regularization

You will now run a logistic regression model on scaled data with L1 regularization to perform feature selection alongside model building. In the video exercise you have seen how the different C values have an effect on your accuracy score and the number of non-zero features. In this exercise, you will set the C value to 0.025.

The LogisticRegression and accuracy_score functions from sklearn library have been loaded for you. Also, the scaled features and target variables have been loaded as train_X, train_Y for training data, and test_X, test_Y for test data.

Initialize a logistic regression with L1 regularization and C value of 0.025.
Fit the model on the training data.
Predict churn values on the test data.
Print the accuracy score of your predicted labels on the test data.

Exercise

Fit logistic regression with L1 regularization

Instructions