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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

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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)
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