Update to work with Python 3.12 and Scikit-Learn >= 1.2 #77
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steppi
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May 9, 2024
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| self.stop = list( | ||
| set(english_stopwords).union([sf.lower() for sf | ||
| in self.shortforms]) | ||
| ) |
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TfidfVectorizer now only allows lists for stop_words and no longer accepts generic containers.
steppi
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May 9, 2024
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| f1_scorer = make_scorer(f1_score, labels=self.pos_labels, | ||
| pos_label=None, |
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Input validation for f1_score and friends now requires explicitly setting pos_label=None when no pos_labels are desired. Before, if average was not binary, pos_label was completely ignored.
steppi
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May 9, 2024
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| feature_names = tfidf.get_feature_names() | ||
| feature_names = tfidf.get_feature_names_out() |
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This method changed names in scikit-learn 1.0, the old one was deprecated and then removed in 1.2.
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Thanks @steppi, this looks great - I tested with Gilda and it works well on Python 3.12. |
This was referenced May 9, 2024
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This PR makes the following changes:
_score.c, instead require Cython as a build dependency.adeft/modeling/classify.pyso that it works with the latest Scikit_learn.This supersedes #76. Hopefully everything in CI passes.