Efficient K-Means Clustering Algorithm Using Feature Weight and Min-Max Normalization

Ei Ei Phyo; Ei Ei Myat

doi:10.7753/ijsea0712.1001

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Efficient K-Means Clustering Algorithm Using Feature Weight and Min-Max Normalization

Ei Ei Phyo Ei Ei Myat

Year: 2018 Journal: International Journal of Science and Engineering Applications Vol: 7 (12)Pages: 479-482

DOI: 10.7753/ijsea0712.1001

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Keywords:

Normalization (sociology) Cluster analysis Computer science Algorithm Feature (linguistics) k-means clustering Pattern recognition (psychology) Artificial intelligence Sociology Social science Philosophy

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Wireless Sensor Networks and IoT

Physical Sciences → Engineering → Control and Systems Engineering

Advanced Algorithms and Applications

Physical Sciences → Engineering → Control and Systems Engineering

Advanced Clustering Algorithms Research

Physical Sciences → Computer Science → Artificial Intelligence

Efficient K-Means Clustering Algorithm Using Feature Weight and Min-Max Normalization

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