Classification evaluation
Moving forward with evaluation metrics, this time you'll evaluate our logistic regression model from before with the goal of predicting the binary RainTomorrow feature using humidity.
We have gone ahead and imported the model as clf and the same test sets assigned to the X_test and y_test variables. Generate and analyze the confusion matrix and then compute both precision and recall before making a conclusion.
This exercise is part of the course
Practicing Statistics Interview Questions in Python
Hands-on interactive exercise
Have a go at this exercise by completing this sample code.
# Generate and output the confusion matrix
from sklearn.metrics import confusion_matrix
preds = clf.predict(X_test)
matrix = confusion_matrix(____, ____)
print(____)