Enhancement of Data Mining Clustering Algorithm Based On Innovative Artificial Intelligence Approach

Abstract

As the technology is increasing day by day huge amount of data is uploaded in the network technology. The main serious problem in this is due to lack of knowledge. Combination of cloud computing and conventional data mining gives the complete data mining structure.  Clustering algorithm is one of the most widely utilized algorithms in cloud data mining’s. Cluster is nothing but mapping of data from one group to another group and there is a clean partition of the specified data. Hence in this paper enhancement of data mining clustering algorithm based on innovative artificial intelligence approach. In clustering algorithms one of the most commonly utilized is FCM algorithm.  Depend on the fuzzy entropy function FCM algorithm is developed. Clustering results are validated based on the F-measure method which is Probability Based Matching (PBM) index. To define the number of clusters there is requirement in FCM algorithm. Different fuzzy partitions are available to define the different cluster values. Compared with the traditional FCM algorithm, introduced fuzzy c-mean algorithm with fuzzy entropy can achieve better performance and the optimum number of clusters can be determined automatically.