关键词: 数据挖掘，多层关联分类器，FP-tree,剪枝，闭频繁模式

Abstract: Focused on the problem that the traditional multi level associative classification mining cause a lot of redundancy rules which affecte the efficiency of classification, this paper presented an improved multi level associative classier based on Class FP-tree named MACCF (Multi-level Associative Classifier based on Class FP-tree). It is to plot the training set based on the class property of records, using CLOSETS generates to complete candidate item set, through the proposal inside and outside prune strategies reduce most of redundancy and has improved the accuracy; adopting cross associative method to solve the cross level classification, experimental results show its high efficiency in classification.

Key words: Data mining, Multi level associative classifier, FP-tree, Prune, CLOSET