An Improved Incremental Mining Algorithm Based on Risk Analysis of the Association Rules for Bank Cost Analysis

Abstract

This paper introduces improving rate and proposes the incremental mining algorithm with the weighted model for optimizing association rules based on CBA mining algorithm. The risk analysis of the strong association rules is proposed for trend forecasting. And the risk degree of the lost rules based on the incremental mining is also analyzed. Comparing with the traditional algorithm, the improved algorithm is fast, efficient in incremental data mining and can find trends in association rules. The decision making reliability is enhanced by the association rules obtained from the improved algorithm. The algorithm was used in bank cost analysis with test results showing that the prediction precision of the algorithm is better than that of the traditional algorithm.