Currently the library is based
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Extra Trees Algorithms
In the Extra Trees algorithm, each tree is trained using the whole learning sample and the splitting in the tree is randomized. The randomness is selected from a uniform distribution within the feature's range. From all the splits, the one with the highest score is chosen to split the node.