Enhanced soft subspace clustering through hybrid dissimilarity

Author:

Wang Lijuan12,Hao Zhifeng1,Cai Ruichu12,Wen Wen1

Affiliation:

1. Faculty of Computer, Guangdong University of Technology, Guangzhou, P.R. China

2. State Key Laboratory for Novel Software Technology, Nanjing University, P.R. China

Publisher

IOS Press

Subject

Artificial Intelligence,General Engineering,Statistics and Probability

Reference26 articles.

1. Maximum ambiguity based sample selection in fuzzy decision tree induction;Wang;IEEE Transactions on Knowledge and Data Engineering,2012

2. A new approach to classifier fusion based on upper integral;Wang;IEEE Transactions on Cybernetics,2014

3. Fusion of extreme learning machine with fuzzy integral;Zhai;International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems,2013

4. Non-naive bayesian classifiers for classification problems with continuous attributes;Wang;IEEE Transactions on Cybernetics,2014

5. An improved algorithm for calculating fuzzy attribute reducts;Zhai;Journal of Intelligent & Fuzzy Systems,2013

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1. Soft Subspace Based Ensemble Clustering for Multivariate Time Series Data;IEEE Transactions on Neural Networks and Learning Systems;2022

2. Adaptive soft subspace clustering combining within-cluster and between-cluster information;Journal of Intelligent & Fuzzy Systems;2020-03-04

3. A rough set based subspace clustering technique for high dimensional data;Journal of King Saud University - Computer and Information Sciences;2020-03

4. Enhanced subspace clustering through combining Minkowski distance and Cosine dissimilarity;Journal of Intelligent & Fuzzy Systems;2018-11-20

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