Data/hora: 23/09/2024 15:53:03

Biblioteca(s): 	Embrapa Agricultura Digital.	
Data corrente: 	13/07/2011	
Data da última atualização: 	14/07/2011	
Autoria: 	BASU, M.; HO, T. K. (ed.).	
Afiliação: 	MITRA BASU, National Science Foundation; TIN KAM HO, Bell Laboratories.	
Título: 	Data complexity in pattern recognition.	
Ano de publicação: 	2006	
Fonte/Imprenta: 	London: Springer, 2006.	
Páginas: 	300 p. il.	
Série: 	(Advanced information and knowledge processing).	
ISBN: 	978-1-84628-171-6	
Idioma: 	Inglês	
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.	
Palavras-Chave: 	Classificadores; Complexidade de dados; Computational complexity; Pattern perception; Pattern recognition systems; Reconhecimento de padrões.	
Thesaurus Nal: 	Classification.	
Categoria do assunto: 	X Pesquisa, Tecnologia e Engenharia	
Registro original: 	Embrapa Agricultura Digital (CNPTIA)	
Exemplares: 	CNPTIA - (15867-1) - ADC - LV - PP - 006.4 - BAS - 2011.00172 - DIS