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Data clustering using enhanced biogeography-based optimization | IEEE Conference Publication | IEEE Xplore

Data clustering using enhanced biogeography-based optimization


Abstract:

Data clustering is one of the important tool in data analysis which partitions the dataset into different groups based on similarity and dissimilarity measures. Clusterin...Show More

Abstract:

Data clustering is one of the important tool in data analysis which partitions the dataset into different groups based on similarity and dissimilarity measures. Clustering is still a NP-hard problem for large dataset due to the presence of irrelevant, overlapping, missing and unknown features which leads to converge it into local optima. Therefore, this paper introduces a novel hybrid meta-heuristic data clustering approach which is based on K-means and biogeography-based optimization (BBO). The proposed method uses K-means to initialize the population of BBO. The simulation has been done on eleven dataset. Experimental and statistical results validate that proposed method outperforms the existing methods.
Date of Conference: 10-12 August 2017
Date Added to IEEE Xplore: 08 February 2018
ISBN Information:
Electronic ISSN: 2572-6129
Conference Location: Noida, India

References

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