sklearn.tree Module

An sklearn.tree Module is an sklearn module of decision-tree learning systems.

• AKA: Scikit-Learn Decision-Tree Class.
• Context:
  • It require to call/select a Decision Tree Learning System :
    • sklearn.tree.Model_Name(self, arguments) or simply sklearn.tree.Model_Name()

      where Model_Name is the name of the selected decision-tree learning system.

• Example(s)
  • sklearn.tree.DecisionTreeClassifier(), a Classification Tree Learning System.
  • sklearn.tree.DecisionTreeRegressor(), a Regression Tree Learning System.
  • sklearn.tree.ExtraTreeClassifier(), a Classification Extra Trees Learning System.
  • sklearn.tree.ExtraTreeRegressor(), a Regression Extra Trees Learning System.
  • …
• Counter-Example(s):
  • sklearn.manifold, a collection of Manifold Learning Systems.
  • sklearn.ensemble, a collection of Decision Tree Ensemble Learning Systems.
  • sklearn.metrics, a collection of Metrics Subroutines.
  • sklearn.covariance,a collection of Covariance Estimators.
  • sklearn.cluster.bicluster, a collection of Spectral Biclustering Algorithms.
  • sklearn.linear_model, a collection of Linear Model Regression Systems.
  • sklearn.neighbors, a collection of K Nearest Neighbors Algorithms.
  • sklearn.neural_network, a collection of Neural Network Systems.
• See: DTree System.

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References

2017

• http://scikit-learn.org/stable/modules/classes.html#module-sklearn.tree
  • QUOTE: The sklearn.tree module includes decision tree-based models for classification and regression.

User guide: See the Decision Trees section for further details.
tree.DecisionTreeClassifier([criterion, …]) 	A decision tree classifier.
tree.DecisionTreeRegressor([criterion, …]) 	A decision tree regressor.
tree.ExtraTreeClassifier([criterion, …]) 	An extremely randomized tree classifier.
tree.ExtraTreeRegressor([criterion, …]) 	An extremely randomized tree regressor.
tree.export_graphviz(decision_tree[, …]) 	Export a decision tree in DOT format.

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