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googledatalab / pydatalab / 2665
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DEFAULT BRANCH: master
Ran 07 Nov 2017 07:35AM UTC
Jobs 1
Files 99
Run time 4s
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Add LIME's tabular explainer to ML Workbench's explainer library. (#602)

LIME's tabular explainer requires a training set to decide the distribution of the perturbed value. That's why "explain_tabular" takes a "trainset" dataframe parameter. When we implement "%%ml explain" for tabular, we will take CSV or BigQuery Dataset as parameter and construct a dataframe from it for users.

5317 of 6818 relevant lines covered (77.98%)

0.78 hits per line

Uncovered Existing Lines

Lines Coverage ∆ File
7
100.0
.tox/coveralls/lib/python2.7/site-packages/google/datalab/contrib/mlworkbench/_prediction_explainer.py
Jobs
ID Job ID Ran Files Coverage
4 2665.4 (TOX_ENV=coveralls) 07 Nov 2017 07:35AM UTC 0
77.98
Travis Job 2665.4
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