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TKDE
2008
197views more  TKDE 2008»
13 years 7 months ago
Agglomerative Fuzzy K-Means Clustering Algorithm with Selection of Number of Clusters
In this paper, we present an agglomerative fuzzy K-Means clustering algorithm for numerical data, an extension to the standard fuzzy K-Means algorithm by introducing a penalty term...
Mark Junjie Li, Michael K. Ng, Yiu-ming Cheung, Jo...
ASC
2008
13 years 7 months ago
Dynamic data assigning assessment clustering of streaming data
: Discovering interesting patterns or substructures in data streams is an important challenge in data mining. Clustering algorithms are very often applied to identify single substr...
Olga Georgieva, Frank Klawonn
IJCAI
2007
13 years 8 months ago
Computation of Initial Modes for K-modes Clustering Algorithm Using Evidence Accumulation
Clustering accuracy of partitional clustering algorithm for categorical data primarily depends upon the choice of initial data points (modes) to instigate the clustering process. ...
Shehroz S. Khan, Shri Kant
KES
2004
Springer
14 years 11 days ago
Multi-modal Data Fusion: A Description
Clustering groups records that are similar to each other into the same group, and those that are less similar into different groups. Clustering data of mixed types is difficult du...
Sarah Coppock, Lawrence J. Mazlack
BMCBI
2006
164views more  BMCBI 2006»
13 years 7 months ago
Evaluation of clustering algorithms for gene expression data
Background: Cluster analysis is an integral part of high dimensional data analysis. In the context of large scale gene expression data, a filtered set of genes are grouped togethe...
Susmita Datta, Somnath Datta