8000 improve error message when passing sample_weight to Pipeline · Issue #13534 · scikit-learn/scikit-learn · GitHub
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jnothman opened this issue Mar 27, 2019 · 3 comments · Fixed by #13536
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improve error message when passing sample_weight to Pipeline #13534

jnothman opened this issue Mar 27, 2019 · 3 comments · Fixed by #13536
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Easy Well-defined and straightforward way to resolve good first issue Easy with clear instructions to resolve help wanted

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@jnothman
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Many estimators take a parameter named sample_weight. Pipeline does not, since it wants its fit parameters to be prefixed by the step name with a __ delimiter:

>>> from sklearn.pipeline import make_pipeline
>>> from sklearn.linear_model import LogisticRegression
>>> clf = make_pipeline(LogisticRegression())
>>> clf.fit([[0], [0]], [0, 1], logisticregression__sample_weight=[1, 1])
Pipeline(memory=None,
     steps=[('logisticregression', LogisticRegression(C=1.0, class_weight=None, dual=False, fit_intercept=True,
          intercept_scaling=1, max_iter=100, multi_class='ovr', n_jobs=1,
          penalty='l2', random_state=None, solver='liblinear', tol=0.0001,
          verbose=0, warm_start=False))])
>>> clf.fit([[0], [0]], [0, 1], sample_weight=[1, 1])
Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
  File "/n/schwafs/home/joel/miniconda3/envs/scipy3k/lib/python3.6/site-packages/sklearn/pipeline.py", line 248, in fit
    Xt, fit_params = self._fit(X, y, **fit_params)
  File "/n/schwafs/home/joel/miniconda3/envs/scipy3k/lib/python3.6/site-packages/sklearn/pipeline.py", line 197, in _fit
    step, param = pname.split('__', 1)
ValueError: not enough values to unpack (expected 2, got 1)

This error message is not friendly enough. It should explicitly describe the correct format for passing sample_weight to a step in a Pipeline.
@jnothman jnothman added Easy Well-defined and straightforward way to resolve good first issue Easy with clear instructions to resolve help wanted labels Mar 27, 2019
@jnothman jnothman mentioned this issue Mar 27, 2019
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@jnothman
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There is some code in gradient boosting that checks for the current error message, so that should be updated to reflect a changed error message too.

(Arguably, this should be a TypeError, not a ValueError, since the user has passed the wrong parameter names, but I'm ambivalent to whether we fix that.)

@okz12
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okz12 commented Mar 28, 2019

I'd like to take this issue.

@okz12 okz12 mentioned this issue Mar 28, 2019
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@jnothman
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jnothman commented Mar 28, 2019 via email

@joybh98 joybh98 mentioned this issue Mar 30, 2019
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[MRG+1] Fix/pipeline param error msg
Improved error message for passing of sample_weight to pipeline
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@jnothman @okz12
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