sklearn.tree.DecisionTreeClassifier

A sklearn.tree.DecisionTreeClassifier is a classification tree learning system within sklearn.tree.

• Context
  • Usage:

1) Import Classification Tree Learning System from scikit-learn : from sklearn.tree import DecisionTreeClassifier

2) Create design matrix X and response vector Y

3) Create Decision Tree Classifier object: DTclf=DecisionTreeClassifier(criterion=’gini’, splitter=’best’[, max_depth=None, min_samples_split=2, min_samples_leaf=1,...])

4) Choose method(s):

• DTclf.apply(X[, check_input]), returns the leaf index for each sample predictor.
• DTclf.decision_path(X[, check_input]), returns the decision path in the tree.
• DTclf.fit(X, y[, sample_weight, check_input,...]) builds a decision tree classifier from the training set (X, y).
• DTclf.get_params([deep]) returns parameters for this estimator.
• DTclf.predict(X[, check_input]), predicts class for X.
• DTclf.predict_log_proba(X), predicts class log-probabilities of the input samples X.
• DTclf.predict_proba(X[, check_input]), predicts class probabilities of the input samples X.
• DTclf.score(X, y[, sample_weight]), returns the mean accuracy on the given test data and labels.
• DTclf.set_params(**params), sets the parameters of this estimator.

• Example(s):
  • Plot the decision surface of a decision tree on the iris dataset
• Counter-Example(s):
  • sklearn.tree.DecisionTreeRegressor
  • sklearn.tree.ExtraTreeRegressor
  • sklearn.tree.ExtraTreeClassifier
• See: Decision Tree, Classification System, Regularization Task, Ridge Regression Task, Kernel-based Classification Algorithm.

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References

2017a

• (Scikit-Learn, 2017A) ⇒ http://scikit-learn.org/stable/modules/generated/sklearn.tree.DecisionTreeClassifier.html Retrieved:2017-10-22
  • QUOTE: class sklearn.tree.DecisionTreeClassifier(criterion=’gini’, splitter=’best’, max_depth=None, min_samples_split=2, min_samples_leaf=1, min_weight_fraction_leaf=0.0, max_features=None, random_state=None, max_leaf_nodes=None, min_impurity_decrease=0.0, min_impurity_split=None, class_weight=None, presort=False)

    A decision tree classifier.

    Read more in the User Guide.

2017b

• (Scikit-Learn, 2017B) ⇒ http://scikit-learn.org/stable/modules/tree.html#classification
  • QUOTE: DecisionTreeClassifier is a class capable of performing multi-class classification on a dataset.

    As with other classifiers, DecisionTreeClassifier takes as input two arrays: an array X, sparse or dense, of size [n_samples, n_features] holding the training samples, and an array Y of integer values, size [n_samples], holding the class labels for the training samples:

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