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A new feature selection method for Gaussian mixture clustering
Hong Zeng,
Yiu Ming CHEUNG
*
*
Corresponding author for this work
Department of Computer Science
Research output
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Contribution to journal
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Journal article
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peer-review
70
Citations (Scopus)
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Dive into the research topics of 'A new feature selection method for Gaussian mixture clustering'. Together they form a unique fingerprint.
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Keyphrases
Gaussian Mixture Clustering
100%
Feature Selection Methods
100%
Model Selection
50%
Weighted Likelihood
50%
Automatic Model Selection
50%
International Conference
50%
Mixture Model Clustering
50%
Video Classification
50%
Expectation-maximization Algorithm
25%
Pattern Recognition
25%
Multimedia
25%
Data Clustering
25%
Number of Components
25%
Feature Selection
25%
Class Label
25%
Gaussian Mixture
25%
Learning Process
25%
Feature Subset
25%
Clustering Approach
25%
Mixture Gaussian
25%
Expo
25%
Penalized EM Algorithm
25%
Clustering Model
25%
Computer Science
Gaussian Mixture
100%
Feature Selection
100%
Experimental Result
16%
Multimedia
16%
Clustered Data
16%
Pattern Recognition
16%
Feature Extraction
16%
Learning Process
16%
clustering approach
16%