期刊名称：International Journal of Innovative Research in Science, Engineering and Technology
印刷版ISSN：2347-6710
电子版ISSN：2319-8753
出版年度：2015
卷号：4
期号：10
页码：9576
DOI：10.15680/IJIRSET.2015.0410013
出版社：S&S Publications
摘要：Data Mining is the process of extracting the information from the raw data. One of the challenging areasin the data mining is the clustering and finding the best cluster is difficult task. The aim of this paper is to find aclustering algorithm which fits with consensus clustering. Consensus clustering is the process of finding the bestclustering from multiple clustering. The problem in consensus clustering is that it doesn’t fit well for all clusteringalgorithm. This paper is to find the best clustering algorithm and it is embedded with consensus clustering. Here wefocus on 3 different algorithms such as k-means algorithm, hierarchical algorithm and graph partitioning algorithm. Themain focus of this paper is to find the algorithm which fits for large datasets. We summarize our observation andidentify the common pitfalls in the previous works.
关键词：Clustering; Consensus Clustering; Data Mining; k-Means; Hierarchical
