Handle binary classifier with all-0 labels #5810
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**Bug**: Currently, cuML RandomForestClassifier fails with error `More than one variable expected for classification problem` when the labels are all 0's. The error arises when the RandomForestClassifier object is translated into a Treelite object. **Minimal reproducer**: ```python from cuml.ensemble import RandomForestClassifier import numpy as np X = np.array([[3, 2], [2, 3]], dtype=np.float32) y = np.array([0, 0], dtype=np.int32) clf = RandomForestClassifier(max_depth=1) clf.fit(X, y) clf.predict(X) # fails here ``` **Fix**. When RandomForestClassifier produces a single output, zero-pad it to length 2 before passing it to Treelite. Authors: - Philip Hyunsu Cho (https://github.com/hcho3) Approvers: - Dante Gama Dessavre (https://github.com/dantegd) URL: rapidsai#5810
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Bug: Currently, cuML RandomForestClassifier fails with error
More than one variable expected for classification problemwhen the labels are all 0's. The error arises when the RandomForestClassifier object is translated into a Treelite object.Minimal reproducer:
Fix. When RandomForestClassifier produces a single output, zero-pad it to length 2 before passing it to Treelite.