Evaluating Students Placement Performance Using Normalized K-Means Clustering Algorithm

Abstract

Ensemble Cluster is verifiedas a worthy alternative in front of theanalysis of the clustering problems. Constructinga cluster for ausing similar dataset and mergingit into a distinct clustering. The mixturing process is useful toextend theclustering quality.Another name of clustering Ensemble is   consensus clustering. ClusterEnsemble providing as a promising solutions for heterogeneous or for multisource data clustering. Spectral ensemble clustering results in used todropped thedifficulty of algorithm.Now weprovide various clusteringmethods applied in same dataset and producedifferent clusteringresults. The several methods feature alldiscussed, it helped in choosing the utmostsuitable one to solve a problem at handOn the preprocessed dataset, clustering isgenerated by using clustering’s namely; normalized k-means, to predict the level of student's performance  inplacement.