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pylablanche / gcForest

Python implementation of deep forest method : gcForest
MIT License
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completely-random tree forests #7

Closed sevenguin closed 6 years ago

sevenguin commented 6 years ago

There are two types of forest in the paper, and the first is completely-random tree forests. I think the forest is show in code crf = RandomForestClassifier(n_estimators=n_tree, max_features=None, min_samples_split=min_samples, oob_score=True, n_jobs=n_jobs) , in function window_slicing_pred_prob, if i'm right, then the parameter max_features should be 1.

pylablanche commented 6 years ago

Hi @sevenguin , Thanks for you comment. I went back to the documentation and indeed setting max_features to 1 makes the classifier a totally random decision tree see documentation. I am now confused about what the deep forest authors meant by "completely random forest". I'll go back to the paper and make corrections if I misunderstood this part.

Thanks again for the feedback

pylablanche commented 6 years ago

@sevenguin , I have double checked the paper and the scikit documentation and you're right about the max_features. It's now corrected and updated. Thanks for noticing!!!