Research Article
DAG-searched and Density-based Initial Centroid Location Method for Fuzzy Clustering of Big Biomedical Data
@INPROCEEDINGS{10.4108/icst.bict.2014.257932, author={Chanpaul Jin Wang and Hua Fang and Honggang Wang}, title={DAG-searched and Density-based Initial Centroid Location Method for Fuzzy Clustering of Big Biomedical Data}, proceedings={8th International Conference on Bio-inspired Information and Communications Technologies (formerly BIONETICS)}, publisher={ICST}, proceedings_a={BICT}, year={2015}, month={2}, keywords={initial centroids fuzzy clustering density directed acycline graph}, doi={10.4108/icst.bict.2014.257932} }- Chanpaul Jin Wang
Hua Fang
Honggang Wang
Year: 2015
DAG-searched and Density-based Initial Centroid Location Method for Fuzzy Clustering of Big Biomedical Data
BICT
ACM
DOI: 10.4108/icst.bict.2014.257932
Abstract
Randomly allocating initial centroids may lead to undesired steady states for fuzzy c-means (FCM) clustering. This paper proposes an alternative method to automatically search initial centroid location based on data density. Specifically, this method auto-searches points located in high-density domains as centroids using directed acycline graph (DAG) based algorithm, and then iteratively fnding the optimal patterns. Compared with random initialization method, our method seems to have the potential to improve FCM accuracy for larger data size with seconds' tradeoff in computational time using published datasets.
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