一种基于关联分类的增量更新算法

针对现有关联分类技术的不足，提出了一种适用于关联分类的增量更新算法IUAC。该算法是基于频繁模式树挖掘和更新关联规则的，并使用一种树形结构来存储最终用于分类的关联规则。同时，增加了对分类规则的约束条件，进一步控制了用于分类的关联规则的数量。最后，对算法整体进行了分析和讨论。

Incremental updating algorithm based on associative classification

Utilizing association rule discovery method to construct classification systems in data mining is known as associative classification.Existing AC techniques mine the training data set as whole in order to produce the outcome.An Incremental Upda- ting algorithm applied to AC technique（IUAC）is introduced.The algorithm is based on the FP-growth to mine and update the association rules.And it applies a tree structure to store the association rules which are mined for classification.Moreover，in this paper，it adds more appropriate constraints in rule ranking procedure in order to control the number of class associative rules and improve the predictive accuracy.And finally，some analyses to the new algorithm are offered.