Add Recursive Feature Elimination Selector component #3934
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## main #3934 +/- ##
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+ Coverage 99.7% 99.7% +0.1%
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Files 346 347 +1
Lines 36719 36755 +36
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+ Hits 36589 36625 +36
Misses 130 130
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rwedge
| hyperparameter_ranges = { | ||
| "perc": Integer(0, 100), | ||
| } | ||
| """{ | ||
| "percent_features": Real(0.01, 1), | ||
| "threshold": ["mean", "median"], | ||
| }""" |
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I think we'd want min_features_to_select and step here but not positive on how this section is mean to be set up
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Yeah, good catch. I overlooked that, but will take a closer look and update.
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I think we should set up step between 0 and 1 so it selects a eliminates a percentage amount (so we can generalize more easily than an integer) but I don't think we need to tune min_features_to_select since RFECV is supposed to find the optimal amount of features. I think a default min_features_to_select=1 is fine unless there's a reason we want RFE to keep more.
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I updated to have step between 0.05 and 0.25 and changed the default for min_features_to_select to 1.
| """Selects relevant features using recursive feature elimination.""" | ||
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| hyperparameter_ranges = { | ||
| "perc": Integer(0, 100), |
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perc isn't used anywhere right? This should be updated with step and other parameters we want to tune.
| Defaults to None. | ||
| n_estimators (float): The number of trees in the forest. Defaults to 100. | ||
| max_depth (int): Maximum tree depth for base learners. Defaults to 6. | ||
| If both percent_features and number_features are specified, take the greater number of features. Defaults to None. |
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thanks for the fix 😄
Add Recursive Feature Elimination Selector component
Adds a new feature selector component that uses scikit-learn's RFECV to perform the selection.