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Fuzzy mixed-prototype clustering algorithm for microarray data analysis
- Source :
- Neurocomputing. 276:42-54
- Publication Year :
- 2018
- Publisher :
- Elsevier BV, 2018.
-
Abstract
- Being motivated by combining the advantages of hyperplane-based pattern analysis and fuzzy clustering techniques, we present in this paper a fuzzy mix-prototype (FMP) clustering for microarray data analysis. By integrating spherical and hyper-planar cluster prototypes, the FMP is capable of capturing latent data models with both spherical and non-spherical geometric structures. Our contributions of the paper can be summarized into three folds: first, the objective function of the FMP is formulated. Second, an iterative solution which minimizes the objective function under given constraints is derived. Third, the effectiveness of the proposed FMP is demonstrated through experiments on yeast and leukemia data sets.
- Subjects :
- 0209 industrial biotechnology
Fuzzy clustering
FMP
Computer Sciences
Microarray analysis techniques
Cognitive Neuroscience
Pattern analysis
02 engineering and technology
computer.software_genre
Fuzzy logic
Computer Science Applications
Data modeling
Datavetenskap (datalogi)
ComputingMethodologies_PATTERNRECOGNITION
020901 industrial engineering & automation
Microarray data analysis
Hyperplane
Artificial Intelligence
0202 electrical engineering, electronic engineering, information engineering
020201 artificial intelligence & image processing
Data mining
Cluster analysis
computer
Mathematics
Subjects
Details
- ISSN :
- 09252312
- Volume :
- 276
- Database :
- OpenAIRE
- Journal :
- Neurocomputing
- Accession number :
- edsair.doi.dedup.....a1447f92975a88f9a803e9b7cdc84277