Update detect_problem_types implementation
#1476
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@@ Coverage Diff @@
## main #1476 +/- ##
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+ Coverage 100.0% 100.0% +0.1%
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Files 223 223
Lines 15019 15024 +5
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+ Hits 15012 15017 +5
Misses 7 7
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bchen1116
requested review from
dsherry,
angela97lin,
freddyaboulton,
christopherbunn,
eccabay and
jeremyliweishih
and removed request for
dsherry and
angela97lin
jeremyliweishih
approved these changes
Nov 30, 2020
freddyaboulton
approved these changes
Nov 30, 2020
dsherry
reviewed
Nov 30, 2020
| @@ -46,7 +45,7 @@ def detect_problem_type(y): | |||
| raise ValueError("Less than 2 classes detected! Target unusable for modeling") | |||
| if num_classes == 2: | |||
| return ProblemTypes.BINARY | |||
| if y.dtype in numeric_dtypes: | |||
| if is_numeric_dtype(y.dtype): | |||
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Got it, thanks @bchen1116 !
I think the ultimate goal is to update this (and all our utilities) to standardize to woodwork (#1229 ) and then check if the "numeric" semantic tag has been applied to the target. (@angela97lin FYI)
dsherry
reviewed
Nov 30, 2020
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fix #1469
Updated this implementation to catch Int64 dtypes. Previously, using
analyze_metadatain looking_glass, if the target data wasInt64, the problem_type would be classified as multiclass as long as there were>2unique values.After using
is_numeric_dtype:Since we drop NaN data, classifying Boolean (nullable) as a numeric dtype is ok, since we'll catch this binary case before determining if it is regression or multiclass.