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TheDigitalFrontier / parallel-decision-trees

Semester project in CS205 Computing Foundations for Computational Science at Harvard School of Engineering and Applied Sciences, spring 2020.
MIT License
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Pass df to tree.fit() rather than constructor #77

Closed johannes-kk closed 4 years ago

johannes-kk commented 4 years ago

Currently the training DataFrame is passed to the DecisionTree or RandomForest constructor. Most APIs pass train and test data to .fit(train_x, train_y), not to the constructor. Make ours consistent with that.

gpestre commented 4 years ago

@johannes-kk see PR #89 Taking X and y separately is less straightforward because I don't think we have an efficient way of dropping the y column from an existing DataFrame, but feel free to give it a try.

johannes-kk commented 4 years ago

No need. Keep it simple to cut down on time. What we have already works.