3Dynamic fuzzy decision tree learning

This chapter is divided into six sections. Section 3.1 analyses the research status of decision tree. In Section 3.2, we present the decision tree methods of dynamic fuzzy lattice. In Section 3.3, we provide dynamic fuzzy decision trees (DFDTs) special attribute processing technique. Section 3.4 presents the pruning strategy of DFDT. In Section 3.5, we introduce the application. The summary of this chapter is in Section 3.6.

3.1Research status of decision trees

3.1.1Overseas research status

1. Decision tree algorithms

An Attribute Value Taxonomies Decision Tree Learning algorithm [1] uses the accuracy of attribute values in instances to construct a decision tree across multiple layers. The algorithm has higher ...

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