Cloud Model-based Data Attributes Reduction for Clustering

XU Ru-zhi; NIE Pei-yao; LIN Pei-guang; CHU Dong-sheng

1st International ICST Workshop on Knowledge Discovery and Data Mining

Research Article

Cloud Model-based Data Attributes Reduction for Clustering

Cite: BibTeX Plain Text

@INPROCEEDINGS{10.4108/wkdd.2008.2633,
    author={XU Ru-zhi and NIE Pei-yao and LIN Pei-guang and CHU Dong-sheng},
    title={Cloud Model-based Data Attributes Reduction for Clustering},
    proceedings={1st International ICST Workshop on Knowledge Discovery and Data Mining},
    publisher={ACM},
    proceedings_a={WKDD},
    year={2010},
    month={5},
    keywords={},
    doi={10.4108/wkdd.2008.2633}
}

XU Ru-zhi
NIE Pei-yao
LIN Pei-guang
CHU Dong-sheng
Year: 2010
Cloud Model-based Data Attributes Reduction for Clustering
WKDD
ACM
DOI: 10.4108/wkdd.2008.2633

XU Ru-zhi¹^,*, NIE Pei-yao¹, LIN Pei-guang¹, CHU Dong-sheng¹

1: School of Information Engineering, Shandong University of Finance, Jinan 250014, P.R. China

*Contact email: rzxu@sdfi.edu.cn

Abstract

Data reduction, which can simplify large scale data and not lose useful information, is an important topic of knowleadge discorvery, data clustering and classification. Aiming to solve the current problem that continuous attribute in algorithm of clustering or classification has to be discrete, a new algorithm of data reduction based on cloud model is put forward. By use of cloud model, this algorithm calculates each conditional attribute’s importance to decision-making attribute( s), and obtains the reduction attributes by virtue of greedy algorithm. This new data reduction algorithm was verified by some experiments and was proved to be stable and efficient.

Published: 2010-05-16
Publisher: ACM
Modified: 2010-05-16

: http://dx.doi.org/10.4108/wkdd.2008.2633