Title :
Non-exclusive Clustering: A Partitioning Approach
Author :
Agarwal, Nitesh ; Ahmed, H.A. ; Bhattacharyya, D.K.
Author_Institution :
Deptt. of Comp. Sc. & Eng., Heritage Inst. of Technol., Kolkata, India
Abstract :
Non-exclusive clustering is a partitioning based clustering scheme wherein the data points are clustered such that they belong to one or more clusters. Usually in real world applications, the datasets that we work with are not entirely exclusive in nature. In applications such as gene expression data analysis and satellite image processing, non-exclusive algorithms need to be employed for better and more accurate cluster analysis. Therefore, we intend to tackle such problems with a non-exclusive clustering algorithm, closely determined by a nonexclusivity score (NES). The NES is based on a feature class correlation measure, which helps to determine the significant overlap between the data points in the dataset and aids us in comprehending the clusters to which they belong to.
Keywords :
genetic algorithms; pattern clustering; NES; cluster analysis; feature class correlation measure; gene expression data analysis; nonexclusive algorithm; nonexclusive clustering algorithm; nonexclusivity score; partitioning approach; partitioning based clustering scheme; satellite image processing; Algorithm design and analysis; Clustering algorithms; Correlation; Laplace equations; Linear programming; Ontologies; Partitioning algorithms; Feature Class Correlation measures; Laplacian Score; Non-exclusive clusters; k-means; p-value;
Conference_Titel :
Emerging Information Technology and Engineering Solutions (EITES), 2015 International Conference on
Conference_Location :
Pune
Print_ISBN :
978-1-4799-1837-9
DOI :
10.1109/EITES.2015.9
