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An improved clustering algorithm based on finite Gaussian mixture model
Zhilin He, Chun Hsing Ho
Civil Engineering, Construction Management, and Environmental Engineering
Research output
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Contribution to journal
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Article
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peer-review
11
Scopus citations
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Dive into the research topics of 'An improved clustering algorithm based on finite Gaussian mixture model'. Together they form a unique fingerprint.
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Keyphrases
Cluster Analysis
20%
Clustering Analysis
20%
Clustering Results
20%
Conditional Entropy
20%
Continuous Distribution
20%
Convergence Rate
20%
Density Distribution
20%
EM Algorithm
60%
Entropy Model
20%
Finite Gaussian Mixture Models
100%
Improved Clustering Algorithm
100%
Incomplete Data
60%
Missing Data
60%
Mixed Density
20%
Novel Algorithm
40%
Number of Components
20%
Penalized Maximum Likelihood Estimation
20%
Mathematics
Approximates
20%
Cluster Analysis
20%
Clustering Algorithm
100%
Conditional Entropy
20%
Continuous Distribution
20%
EM Algorithm
60%
Gaussian Mixture Model
100%
Incomplete Data
60%
Maximum Likelihood Estimation
20%
Computer Science
Cluster Analysis
20%
Clustering Algorithm
100%
Clustering Analysis
20%
Clustering Result
20%
Conditional Entropy
20%
Continuous Distribution
20%
Convergence Speed
20%
Experimental Result
20%
Gaussian Mixture Model
100%
Likelihood Estimation
20%
maximum-likelihood
20%