changes for parents pressure for selection #22
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lacava
requested changes
Jun 14, 2017
few/tests/test_few.py
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| few_score = learner.score(features[:300], target[:300]) | ||
| test_score = learner.score(features[300:],target[300:]) | ||
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| lasso = LassoLarsCV() |
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you can remove the lasso model fitting.
few/tests/test_few.py
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| lasso_score = lasso.score(features[:300], target[:300]) | ||
| print("few score:",few_score,"lasso score:",lasso_score) | ||
| print("few test score:",test_score,"lasso test score:",lasso.score(features[300:],target[300:])) | ||
| assert few_score >= lasso_score |
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you don't need to check the score with an assertion
few/variation.py
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| elif hasattr(self.ml,'feature_importances_'): | ||
| # for tree methods, filter our individuals with 0 feature importance | ||
| offspring = copy.deepcopy(list(x for i,x in zip(self.ml.feature_importances_, self.valid(parents)) if i != 0)) | ||
| if self.weight_parents: | ||
| weights = abs(self.ml.feature_importances_) |
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feature importances are always positive so you can remove the abs() from this one
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