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.
This exercise is part of the course
Dimensionality Reduction in Python
Hands-on interactive exercise
Have a go at this exercise by completing this sample code.
# Sum the votes of the three models
votes = ____
print(votes)