IMECH-IR  > 力学所知识产出(1956-2008)
Fuzzy Classification Using Self-Organizing Map and Learning Vector Quantization
Chen N(陈宁); Chen, N (reprint author), Univ Nova Lisboa, Fac Ciencias & Tecnol, P-1200 Lisbon, Portugal.
Source PublicationDATA MINING AND KNOWLEDGE MANAGEMENT
2004
Volume3327Pages:41-50
ISSN0302-9743
AbstractFuzzy classification proposes an approach to solve uncertainty problem in classification tasks. It assigns an instance to more than one class with different degrees instead of a definite class by crisp classification. This paper studies the usage of fuzzy strategy in classification. Two fuzzy algorithms for sequential self-organizing map and learning vector quantization are proposed based on fuzzy projection and learning rules. The derived classifiers are able to provide fuzzy classes when classifying new data. Experiments show the effectiveness of proposed algorithms in terms of classification accuracy.
KeywordFuzzy Classification Self-organizing Map (Som) Learning Vector Quantization (Lvq)
Indexed BySCI
Language英语
WOS IDWOS:000227493600005
WOS Research AreaComputer Science
WOS SubjectComputer Science, Artificial Intelligence ; Computer Science, Information Systems
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Document Type期刊论文
Identifierhttp://dspace.imech.ac.cn/handle/311007/58463
Collection力学所知识产出(1956-2008)
Corresponding AuthorChen, N (reprint author), Univ Nova Lisboa, Fac Ciencias & Tecnol, P-1200 Lisbon, Portugal.
Recommended Citation
GB/T 7714
Chen N,Chen, N . Fuzzy Classification Using Self-Organizing Map and Learning Vector Quantization[J]. DATA MINING AND KNOWLEDGE MANAGEMENT,2004,3327:41-50.
APA 陈宁,&Chen, N .(2004).Fuzzy Classification Using Self-Organizing Map and Learning Vector Quantization.DATA MINING AND KNOWLEDGE MANAGEMENT,3327,41-50.
MLA 陈宁,et al."Fuzzy Classification Using Self-Organizing Map and Learning Vector Quantization".DATA MINING AND KNOWLEDGE MANAGEMENT 3327(2004):41-50.
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