Association Rule Based Pattern Analysis with Liver and Diabetes Dataset | Original Article

ABSTRACT:

Association rule mining is important tool for data analysis. The associations rule mining technique finds the relation between two different attributes on the basis of support and confidence value. The association rule mining technique gives two algorithms for analysis of data, one is memory based and the other is memory independent. The memory based algorithm is well known algorithm called apriori algorithm and memory impendent algorithm is called FP-growth algorithm. The rough set based rule generation technique is a new approach for classification. In this technique rough set generates a number of rules, these generated rules design the class builder and finally data are classified. The rough set based classification technique reduces the number of attributes during the classification process. For the optimization and better prediction of classification gravitational search optimization technique in combination of rough set theory is used This paper discusses the rough set theory, rule generation algorithm and Gravitational Search Algorithm (GSA), proposed algorithm and proposed model for the classification process.