Title :
Analysis of X-means and global k-means USING TUMOR classification
Author :
Kumar, Parvesh ; Wasan, Siri Krishan
Author_Institution :
Dept. of Comput. Sci., Maharaja Surajmal Inst., Delhi, India
Abstract :
Clustering is an important data mining technique to extract useful information from various high dimensional datasets. A wide range of clustering algorithms is available in literature and still an open area for researcher. K-means algorithm is one of the basic and most simple partitioning clustering technique.is given by MacQueen in 1967 and aim of this clustering algorithm is to divide the dataset into disjoint clusters. After that many variations of k-means algorithm are given by different authors. Here in this paper we make analysis of two variant of k-means namely global k-means and x-means over colon dataset.
Keywords :
data mining; medical computing; pattern clustering; tumours; X-mean analysis; colon dataset; data mining technique; global k-mean analysis; high dimensional datasets; information extraction; partitioning clustering technique; tumor classification; Cancer; Clustering algorithms; Colon; Computer science; Data mining; Electronic mail; Gene expression; Neoplasms; Partitioning algorithms; Unsupervised learning; Clustering; Datamining; X-means; global k-means;
Conference_Titel :
Computer and Automation Engineering (ICCAE), 2010 The 2nd International Conference on
Conference_Location :
Singapore
Print_ISBN :
978-1-4244-5585-0
Electronic_ISBN :
978-1-4244-5586-7
DOI :
10.1109/ICCAE.2010.5451883
