Clustering Analysis of Simple K a?? Means Algorithm for Various Data Sets in Function Optimization Problem (Fop) of Evolutionary Programming

摘要

Evolutionary Algorithms are based on some influential principles like Survival of the Fittest and with some natural phenomena in Genetic Inheritance. The key for searching the solution in improved function optimization problems are based only on Selection and Mutation operators. In this paper a Selection algorithm for data set is chosen so as to identify the survival of the fittest and also the simple K means clustering algorithm is analyzed on different data sets to check for the performance of the K – means on different data set which gives best accuracy to identify the best solution.