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neural-trees 0.8.0

  • Installation
  • User guide
  • Explaining a prediction
  • Comparing classifiers
  • Against the field
    • Design decisions
    • Performance
    • API reference
    • Examples
    • Changelog
  • GitHub
  • PyPI
  • Installation
  • User guide
  • Explaining a prediction
  • Comparing classifiers
  • Against the field
  • Design decisions
  • Performance
  • API reference
  • Examples
  • Changelog
  • GitHub
  • PyPI

Section Navigation

  • neural_trees.SoftDecisionTree
  • neural_trees.SoftDecisionTreeRegressor
  • neural_trees.NumpySoftTree
  • neural_trees.HardRegressionTree
  • neural_trees.MultivariateDecisionTree
  • neural_trees.OmnivariateDecisionTree
  • neural_trees.HardDecisionTree
  • neural_trees.HierarchicalMixtureOfExperts
  • neural_trees.HardRoutedExperts
  • neural_trees.GALNetwork
  • neural_trees.WeightedKNN
  • neural_trees.NaiveBayesClassifier
  • neural_trees.combined_5x2cv_f_test
  • neural_trees.mcnemar_test
  • neural_trees.paired_t_test
  • neural_trees.Explanation
  • neural_trees.GateStep
  • neural_trees.Counterfactual
  • API reference
  • neural_trees.GateStep

neural_trees.GateStep#

class neural_trees.GateStep(node: int, went: str, probability: float, terms: List[Dict[str, float]], arrival: float)[source]#

Bases: object

One gate on the dominant path.

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  • GateStep
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