Add Plot for Prediction vs Actual for Regression Problems #1252
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## main #1252 +/- ##
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Coverage 99.93% 99.93%
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Files 207 207
Lines 13055 13142 +87
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+ Hits 13046 13133 +87
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added 3 commits
October 1, 2020 15:13
bchen1116
commented
Oct 1, 2020
evalml/model_understanding/graphs.py
Outdated
| data = pd.concat([pd.Series(predictions), | ||
| pd.Series(actual)], axis=1) | ||
| data.columns = ['prediction', 'actual'] | ||
| data['outlier'] = np.where((abs(data['prediction'] - data['actual']) >= outlier_threshold), "#ffff00", "#0000ff") |
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needed to encode colors as hex values
bchen1116
requested review from
freddyaboulton,
angela97lin,
dsherry,
christopherbunn,
eccabay and
jeremyliweishih
and removed request for
freddyaboulton
angela97lin
previously requested changes
Oct 1, 2020
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Looking good but I have two immediate comments:
- It would be helpful to post an image of what this looks like or add it to the model_understanding docs and link to that instead!
- I see in the original issue (Add predicted vs actual plot (regression) #772) that we want to support regression and timeseries data. Not sure what the updated requirements were but if this PR adds just for regression (which is fine), could you please file a separate issue to make sure timeseries data doesn't get dropped?
freddyaboulton
approved these changes
Oct 2, 2020
freddyaboulton
approved these changes
Oct 5, 2020
added 2 commits
October 5, 2020 11:01
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Submitted issue #1258 to handle adding plot for timeseries. |
Merged
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fix #772
Added
outlier_thresholdfor simple outlier detectionUpdated Model_Understanding doc here
Regular documentation here