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Registro Completo |
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Biblioteca(s): |
Embrapa Agricultura Digital. |
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Data corrente: |
13/07/2011 |
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Data da última atualização: |
14/07/2011 |
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Autoria: |
BASU, M.; HO, T. K. (ed.). |
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Afiliação: |
MITRA BASU, National Science Foundation; TIN KAM HO, Bell Laboratories. |
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Título: |
Data complexity in pattern recognition. |
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Ano de publicação: |
2006 |
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Fonte/Imprenta: |
London: Springer, 2006. |
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Páginas: |
300 p. il. |
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Série: |
(Advanced information and knowledge processing). |
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ISBN: |
978-1-84628-171-6 |
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Idioma: |
Inglês |
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Conteúdo: |
Measures of geometrical complexity in classification problems. Object representation, sample size and dataset complexity. Measures of data and classifier complexity and the training sample size. Linear separability in descent procedures for linear classifiers. Data complexity, margin-based learning and Popper?s philosophy of inductive learning. Data complexity and evolutionary learning. Classifier domains of competence in data complexity space. Data complexity issues in grammatical inference. Simple statistics for complex feature spaces. Polynomial time complexity graph distance computation for web content mining. Data complexity in clustering analysis for gene microarray expression profiles. Complexity of magnetic resonance spectrum classification. Data complexity in tropical cyclone positioning and classification. Human-computer interaction for complex pattern recognition problems. Complex image recognition and web security. |
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Palavras-Chave: |
Classificadores; Complexidade de dados; Computational complexity; Pattern perception; Pattern recognition systems; Reconhecimento de padrões. |
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Thesaurus Nal: |
Classification. |
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Categoria do assunto: |
X Pesquisa, Tecnologia e Engenharia |
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Marc: |
LEADER 01615nam a2200241 a 4500
001 1895862
005 2011-07-14
008 2006 bl uuuu 00u1 u #d
020 $a978-1-84628-171-6
100 1 $aBASU, M.
245 $aData complexity in pattern recognition.
260 $aLondon: Springer$c2006
300 $a300 p. il.
490 $a(Advanced information and knowledge processing).
520 $aMeasures of geometrical complexity in classification problems. Object representation, sample size and dataset complexity. Measures of data and classifier complexity and the training sample size. Linear separability in descent procedures for linear classifiers. Data complexity, margin-based learning and Popper?s philosophy of inductive learning. Data complexity and evolutionary learning. Classifier domains of competence in data complexity space. Data complexity issues in grammatical inference. Simple statistics for complex feature spaces. Polynomial time complexity graph distance computation for web content mining. Data complexity in clustering analysis for gene microarray expression profiles. Complexity of magnetic resonance spectrum classification. Data complexity in tropical cyclone positioning and classification. Human-computer interaction for complex pattern recognition problems. Complex image recognition and web security.
650 $aClassification
653 $aClassificadores
653 $aComplexidade de dados
653 $aComputational complexity
653 $aPattern perception
653 $aPattern recognition systems
653 $aReconhecimento de padrões
700 1 $aHO, T. K.
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Registro original: |
Embrapa Agricultura Digital (CNPTIA) |
