An Ensemble Model For Medical Using Datamining Algorithms

Clustering is the process of grouping data into clusters, where objects within each cluster have high similarity, but are dissimilar to the objects in other clusters. The K- means algorithm is used for clustering large sets of data. The accuracy of the K-means depends upon the selection of Centroids. The execution of the standard K-means algorithm need to reassign the data points a number of times, during every iteration of the loop. The hybrid approach that includes both K means algorithm and genetic algorithm yields good result in the process of clustering. In this study, we proposed an implementation of genetic algorithm which we investigate the quality of clustering technique compared with standard K-means clustering algorithm.