• 人工智能 •

### 基于粗糙集和单事务项组合的关联规则挖掘算法

1. (西北师范大学数学与信息科学学院　甘肃730070) (西北工业大学计算机学院　西安710072)
• 出版日期:2018-12-01 发布日期:2018-12-01

### Algorithm of Mining Association Rules Based on Rough Sets and Transaction Itemsets Combination

• Online:2018-12-01 Published:2018-12-01

Abstract: The Apriori algorithm contains weaknesses such as often requiring a large number of repeated passes over the database to generate the frequent item sets and does not support the incremental updating. To solve these problems, a novel algorithm was proposed in this paper which is based on rough sets, single transaction combination itemsets and set operations for mining. It firstly uses the rough sets to reduce attributes, and then combines data item to each itemset from new decision table and marks it's tags. Finally, it calculates the support and confidence using set operations. This novel algorithm just needs to scanning the decision table only once, while effectively supporting the update of association rules mining. The results of application and experiments show that this novel algorithm is better than Apriori algorithm, it is an effective and fast algorithm for mining association rules.

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