Package weka.classifiers.trees


package weka.classifiers.trees
  • Classes
    Class
    Description
    Class for generating an alternating decision tree.
    Class for building a best-first decision tree classifier.
    Class for building and using a decision stump.
    Classifier for building 'Functional trees', which are classification trees that could have logistic regression functions at the inner nodes and/or leaves.
    Class for constructing an unpruned decision tree based on the ID3 algorithm.
    Class for generating a pruned or unpruned C4.5 decision tree.
    Class for generating a grafted (pruned or unpruned) C4.5 decision tree.
    Class for generating a multi-class alternating decision tree using the LogitBoost strategy.
    Classifier for building 'logistic model trees', which are classification trees with logistic regression functions at the leaves.
    M5Base.
    Class for generating a decision tree with naive Bayes classifiers at the leaves.

    For more information, see

    Ron Kohavi: Scaling Up the Accuracy of Naive-Bayes Classifiers: A Decision-Tree Hybrid.
    Class for constructing a forest of random trees.

    For more information see:

    Leo Breiman (2001).
    Class for constructing a tree that considers K randomly chosen attributes at each node.
    Fast decision tree learner.
    Class implementing minimal cost-complexity pruning.
    Note when dealing with missing values, use "fractional instances" method instead of surrogate split method.

    For more information, see:

    Leo Breiman, Jerome H.
    Interactively classify through visual means.