feat: enhance logging and memory management across modules
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@@ -50,14 +50,18 @@ class LightGBMModel(TraditionalModel):
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self.vectorizers[feature_key] = CountVectorizer(
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analyzer="char", ngram_range=(2, 3), max_features=50
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)
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char_features = self.vectorizers[feature_key].fit_transform(
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column.fillna("").astype(str)
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).toarray()
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char_features = (
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self.vectorizers[feature_key]
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.fit_transform(column.fillna("").astype(str))
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.toarray()
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)
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else:
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# Subsequent times - use existing vectorizer
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char_features = self.vectorizers[feature_key].transform(
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column.fillna("").astype(str)
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).toarray()
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char_features = (
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self.vectorizers[feature_key]
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.transform(column.fillna("").astype(str))
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.toarray()
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)
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features.append(char_features)
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else:
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