Combining 3 feature selectors
We'll combine the votes of the 3 models you built in the previous exercises, to decide which features are important into a meta mask. We'll then use this mask to reduce dimensionality and see how a simple linear regressor performs on the reduced dataset.
The per model votes have been pre-loaded as lcv_mask, rf_mask, and gb_mask and the feature and target datasets as X and y.
Diese Übung ist Teil des Kurses
Dimensionality Reduction in Python
Interaktive Übung
Vervollständige den Beispielcode, um diese Übung erfolgreich abzuschließen.
# Sum the votes of the three models
votes = ____
print(votes)