程序包 weka.classifiers.trees
package weka.classifiers.trees
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类类说明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.