Create a confusion matrix
As you saw in the video, a confusion matrix can be used to determine how well your model is performing. However, before creating the confusion matrix, you need to classify the predicted probabilities as 1 or 0, by using a cut-off.
Note: 1 means Inactive while 0 is Active.
prediction_test, which contains the predicted probabilities of turnover for all cases in test_set is available in your workspace.
Questo esercizio fa parte del corso
HR Analytics: Predicting Employee Churn in R
Istruzioni dell'esercizio
- Turn the numeric predictions in
prediction_testinto a vector of categorical predictions using a cut-off of 0.5. - Create the confusion matrix using
prediction_categoriesand actual values in the test set (test_set$turnover).
Esercizio pratico interattivo
Prova a risolvere questo esercizio completando il codice di esempio.
# Classify predictions using a cut-off of 0.5
prediction_categories <- ___(prediction_test > 0.5, 1, 0)
# Construct a confusion matrix
conf_matrix <- ___(prediction_categories, test_set$turnover)
conf_matrix