IMECH-IR  > 力学所知识产出(1956-2008)
Fuzzy classification using self-organizing map and learning vector quantization
Chen N; Chen, N (reprint author), Univ Nova Lisboa, Fac Ciencias & Tecnol, P-1200 Lisbon, Portugal.
Source PublicationDATA MINING AND KNOWLEDGE MANAGEMENT
2004
Conference NameChinese-Academy-of-Sciences Symposium on Data Minning and Knowledge Management
Conference DateJUL 12-14, 2004
Conference PlaceBeijing, PEOPLES R CHINA
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.
WOS IDWOS:000227493600005
ISBN3-540-23987-1
Indexed ByCPCI-S
Language英语
Citation statistics
Cited Times:4[WOS]   [WOS Record]     [Related Records in WOS]
Document Type会议论文
Identifierhttp://dspace.imech.ac.cn/handle/311007/58913
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[C]DATA MINING AND KNOWLEDGE MANAGEMENT,2004.
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