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Fast Differentiable Forest lib with the advantages of both decision trees and neural networks

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Have that feature to use on Kaggle? Any instructions?

It's strange that the best accuracy is smallest number. something wrong?

--------------------------------------------------------------------------- AttributeError Traceback (most recent call last) in ----> 1 learner.predict(ze.values) /kaggle/input/quantumforest1/python-package/quantum_forest/QForest_Net.py in predict(self, X_, pred_leaf, pred_contrib, raw_score, num_iteration, flag) 426 The predicted values. 427 """ --> 428 self.profile.Snapshot("PRED_0") 429...

Looks like an interesting project, how about packaging this up for easy install via pip? or failing that some installation instructions on the README