A Decision Tree Algorithm for Ordinal Classification
In many classiffication problems the domains of the attributes and the classes are linearly orderded. For such problems the classiffication rule often needs to be order-preserving or monotone as we call it. Since the known decision tree methods generate non-monotone trees, these methods are not suitable for monotone classiffication problems. We provide an order-preserving tree-generation algorithm for multi-attribute classiffication problems with k linearly ordered classes, and an algorithm for repairing non-monotone decision trees. The performance of these algorithms is tested on random monotone datasets.
KeywordsDecision Tree Class Label Input Space Maximal Element Average Path Length
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