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sklearn.tree.tree.ExtraTreeClassifier
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sklearn.tree.tree.ExtraTreeClassifier

Visibility: public Uploaded 13-08-2021 by Sergey Redyuk sklearn==0.18.1 numpy>=1.6.1 scipy>=0.9 15 runs
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  • openml-python python scikit-learn sklearn sklearn_0.18.1
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An extremely randomized tree classifier. Extra-trees differ from classic decision trees in the way they are built. When looking for the best split to separate the samples of a node into two groups, random splits are drawn for each of the `max_features` randomly selected features and the best split among those is chosen. When `max_features` is set 1, this amounts to building a totally random decision tree. Warning: Extra-trees should only be used within ensemble methods.

Parameters

class_weightdefault: null
criteriondefault: "gini"
max_depthdefault: 1000
max_featuresdefault: "auto"
max_leaf_nodesdefault: null
min_impurity_splitdefault: 1e-07
min_samples_leafdefault: 1
min_samples_splitdefault: 2
min_weight_fraction_leafdefault: 0.0
random_statedefault: null
splitterdefault: "random"

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