Clustering mixed numeric and categorical data with artificial bee colony strategy-Reference-Cited by-同舟云学术

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Clustering mixed numeric and categorical data with artificial bee colony strategy

Published:2019-03-16 Issue:2 Volume:36 Page:1521-1530
ISSN:1064-1246
Container-title:Journal of Intelligent & Fuzzy Systems
language:
Short-container-title:IFS

Author:

Ji Jinchao¹²³⁴,Chen Yongbing¹²³,Feng Guozhong¹²³,Zhao Xiaowei¹²³,He Fei¹²³⁴

Affiliation:

1. School of Information Science and Technology, Northeast Normal University, Changchun, China

2. Institute of Computational Biology, Northeast Normal University, Changchun, China

3. Key Laboratory of Intelligent Information Processing of Jilin Universities, Northeast Normal University, Changchun, China

4. Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of Education, Jilin University, Changchun, China

Publisher

IOS Press

Subject

Artificial Intelligence,General Engineering,Statistics and Probability

Reference35 articles.

1. A k-mean clustering algorithm for mixed numeric and categorical data;Ahmad;Data & Knowledge Engineering,2007

2. Chaotic bee colony algorithms for global numerical optimization;Alatas;Expert Systems with Applications,2010

3. Chaos embedded particle swarm optimization algorithms, Chaos;Alatas;Solitons & Fractals,2009

4. J. C. Bezdek , R. Ehrlich and W. Full , Fcm: the fuzzy c-means clustering algorithm Computers & Geosciences 10 (1984), 191–203.

5. Fuzzy Models and Algorithms for Pattern Recognition and Image Processing

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1. Mixed data clustering based on a number of similar features;Pattern Recognition;2023-11

2. A Multi-View Clustering Algorithm for Mixed Numeric and Categorical Data;IEEE Access;2021

3. Discovering Similarity Across Heterogeneous Features;International Journal of Data Warehousing and Mining;2020-10

4. Improved Artificial Bee Colony Using Sine-Cosine Algorithm for Multi-Level Thresholding Image Segmentation;IEEE Access;2020

5. Clustering Mixed Numeric and Categorical Data With Cuckoo Search;IEEE Access;2020

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