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Class Imbalance Data Check for Severe imbalance - #1905
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## main #1905 +/- ##
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bchen1116
marked this pull request as ready for review
March 1, 2021 21:19
bchen1116
requested review from
ParthivNaresh,
angela97lin,
chukarsten,
dsherry,
freddyaboulton and
jeremyliweishih
and removed request for
angela97lin and
dsherry
March 1, 2021 21:20
freddyaboulton
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Mar 2, 2021
freddyaboulton
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@bchen1116 This looks good to me!
dsherry
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Mar 2, 2021
| if len(below_threshold) and len(sample_counts): | ||
| sample_count_values = sample_counts.index.tolist() | ||
| severe_imbalance = [v for v in sample_count_values if v in below_threshold] | ||
| warning_msg = "The following labels have severe class imbalance because they fall under {:.0f}% of the target and have less than {} samples: {}" |
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Nit-pick: "The following labels in the target have severe class imbalanced because" etc
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part 1 of #1864
Added check to support our severe class imbalance scenario for the new datasplitter.
Still need to address how to find multiclass class imbalances, but I'll leave that for a future PR since I think we need to discuss the best way for identifying that.