Fuzzy improved genetic k-means algorithm
Arezoo Bozorgnia, Samaneh Hajy Mahdizadeh Zargar, Mohammad Hossein Yaghmaee · Iranian Conference on Electrical Engineering · 2011
Clustering is a significant technique in data mining. Many methods for increasing the ability of clustering large data have been presented, one appropriate technique is the k-means method which has been combined with Artificial intelligence methods like genetic algorithm and has created an optimal performance. In primary clustering algorithms the clustering result depends on the initial centers of the clusters. In the presentation of an optimized clustering technique, apart from considering the current issues of clustering, it has tried to find the optimized number of clusters in the clustering procedure. The proposed technique increases the performance and integration of the k-means genetic algorithm with the use of fuzzy methods.