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Facing the same question. @Sandy4321
Unfortunately, in your example, the code to_drop = [column for column in upper.columns if any(upper[column].abs() > correlation_threshold)](in line 201 of feature_selector.py) will remove 2 features, remaining the 1st feature in the upper triangular correlation matrix.
Does it?
May you clarify what are you doing with colinear features
What you remove from let's say 3 similar features
Which one?
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