8000 An error is thrown when using Random forest classifier multi-target non-numeric classes · Issue #11451 · scikit-learn/scikit-learn · GitHub
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An error is thrown when using Random forest classifier multi-target non-numeric classes #11451
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@mitar

Description

@mitar

Description

Random forest classifier can be fit on multiple target columns where columns have string labels and are not numeric, but when trying to predict, an error is thrown.

Steps/Code to Reproduce

import numpy as np
from sklearn.datasets import make_classification
from sklearn.ensemble.forest import RandomForestClassifier

c = RandomForestClassifier()

X, y = make_classification()
y = np.array(['foo' if v else 'bar' for v in y]).reshape((y.shape[0], 1))
ys = np.hstack([y, y])

c.fit(X, ys)
c.predict(X)

Expected Results

No error is thrown.

Actual Results

  File ".../local/lib/python2.7/site-packages/sklearn/ensemble/forest.py", line 550, in predict
    axis=0)
ValueError: could not convert string to float: foo

Versions

Linux-4.13.0-45-generic-x86_64-with-Ubuntu-17.10-artful
('Python', '2.7.14 (default, Sep 23 2017, 22:06:14) \n[GCC 7.2.0]')
('NumPy', '1.14.5')
('SciPy', '1.1.0')
('Scikit-Learn', '0.19.1')

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