Exercise

Model performance

You're now going to evaluate the model from the previous lesson against the test-data.

Evaluating data against new, unseen data is important, as it proves the ability of the model to correctly estimate data it has never encountered before.

All necessary modules have been imported, and the data is available as X_train and y_train, and X_test and y_test respectively.

Instructions

100 XP
  • Create a LogisticRegression model.
  • Fit the model to X_train and y_train.
  • Score the model using X_train and y_train.
  • Score the model using X_test and y_test.