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Add --no_balance
flag to not balance datasets
#287
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AlexTMallen
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add inlp max iterations
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commit ec63dfdd5cc4b4e9b00b33bb5fb95919f261e6ad
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Original file line number | Diff line number | Diff line change |
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@@ -6,7 +6,7 @@ | |
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def train_supervised( | ||
data: dict[str, tuple], device: str, mode: str | ||
data: dict[str, tuple], device: str, mode: str, max_inlp_iter: int | None = None | ||
There was a problem hiding this comment. Choose a reason for hiding this commentThe reason will be displayed to describe this comment to others. Learn more. that's a new feature not related to the balancing either, right? |
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) -> list[Classifier]: | ||
Xs, train_labels = [], [] | ||
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@@ -26,7 +26,7 @@ def train_supervised( | |
lr_model.fit_cv(X, train_labels) | ||
return [lr_model] | ||
elif mode == "inlp": | ||
return Classifier.inlp(X, train_labels).classifiers | ||
return Classifier.inlp(X, train_labels, max_inlp_iter).classifiers | ||
elif mode == "single": | ||
lr_model = Classifier(X.shape[-1], device=device) | ||
lr_model.fit(X, train_labels) | ||
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That's just some refactoring which has nothing to do with the balancing I guesS?
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right, I also added a max_iter flag and this was a necessary refactoring