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fabianegli
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Reference Issue

What does this implement/fix? Explain your changes.

Added type checking of n_estimators and made the corresponding error message explicit about the type issue.

I used the Type checking currently proposed in issue #7394

Any other comments?

I got the intended behavior when testing with rf.fit(n_estimators=100), which works as expeced, and rf.fit(n_estimators='100') which throws the type error as expected.

Example error message with traceback:

Traceback (most recent call last):
File "", line 1, in
File "/Library/Frameworks/Python.framework/Versions/3.5/lib/python3.5/site-packages/sklearn/ensemble/forest.py", line 247, in fit
self._validate_estimator()
File "/Library/Frameworks/Python.framework/Versions/3.5/lib/python3.5/site-packages/sklearn/ensemble/base.py", line 61, in _validate_estimator
"got {0}.".format(type(self.n_estimators)))
ValueError: n_estimators must be an integer, got <class 'str'>.

@agramfort
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you need to add a test and see why travis is not happy

@raghavrv
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Travis failure is a flake8 issue. You need to add a test for both normal python ints as well as numpy scalar integer like the one at #7394

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3 participants