Relevant Feature Selection
Mostrando 1-9 de 9 artigos, teses e dissertações.
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1. A decision-tree-based model for evaluating the thermal comfort of horses
Thermal comfort is of great importance in preserving body temperature homeostasis during thermal stress conditions. Although the thermal comfort of horses has been widely studied, there is no report of its relationship with surface temperature (T S). This study aimed to assess the potential of data mining techniques as a tool to associate surface temperature
Sci. agric. (Piracicaba, Braz.). Publicado em: 2013-12
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2. Seleção de características por meio de algoritmos genéticos para aprimoramento de rankings e de modelos de classificação / Feature selection by genetic algorithms to improve ranking and classification models
Content-based image retrieval (CBIR) and classification systems rely on feature vectors extracted from images considering specific visual criteria. It is common that the size of a feature vector is of the order of hundreds of elements. When the size (dimensionality) of the feature vector is increased, a higher degree of redundancy and irrelevancy can be obse
Publicado em: 2011
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3. Feature selection and intrinsically multivariate prediction in gene regulatory networks identification / Seleção de características e predição intrinsecamente multivariada em identificação de redes de regulação gênica
Feature selection is a crucial topic in pattern recognition applications, especially in bioinformatics, where problems usually involve data with a large number of variables and small number of observations. The present work addresses feature selection aspects in the problem of gene regulatory network identification from expression profiles. Particularly, we
Publicado em: 2008
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4. Analysis of the Clustering Algorithms for the Databases / Análise de Algoritmos de Agrupamento para Base de Dados Textuais
The increasing amount of digitally stored texts makes necessary the development of computational tools to allow the access of information and knowledge in an efficient and efficacious manner. This problem is extremely relevant in biomedicine research, since most of the generated knowledge is translated into scientific articles and it is necessary to have the
Publicado em: 2008
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5. OtimizaÃÃo Global em Redes Neurais Artificiais / Global Optimization in Artificial Neural Networks
Esta tese apresenta um mÃtodo de otimizaÃÃo global e local, baseado na integraÃÃo das heurÃsticas das tÃcnicas Simulated Annealing, Tabu Search, Algoritmos GenÃticos e Backpropagation. O desempenho deste mÃtodo à investigado na otimizaÃÃo simultÃnea da topologia e dos valores dos pesos das conexÃes entre as unidades de processamento de redes ne
Publicado em: 2008
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6. Reconhecimento de padrões proteômicos e genômicos por aprendizagem de máquinas para o disgnóstico médico. / Employ machine learning to unveil encrypted molecular patterns within proteomic and genomic profiles to assist in personalized medical diagnosis.
Motivation: Employ machine learning to unveil encrypted molecular patterns within proteomic and genomic profiles to assist in personalized medical diagnosis. Results and conclusions: 1. Proteomic profile studies: Patients with Hodgkins disease (HD), a rare type of lymphoma, had their serum proteomic profile compared to control subjects (CS) in order to searc
Publicado em: 2005
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7. Relevant feature selection and construction for machine learning. / Seleção e construção de features relevantes para o aprendizado de máquina.
No Aprendizado de Máquina Supervisionado - AM - é apresentado ao algoritmo de indução um conjunto de instâncias de treinamento, no qual cada instância é um vetor de features rotulado com a classe. O algoritmo de indução tem como tarefa induzir um classificador que será utilizado para classificar novas instâncias. Algoritmos de indução convencion
Publicado em: 2000
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8. Metabolic fuel selection: the importance of being flexible
Studies in genetically engineered mice have shown the importance of cross-talk between organs in the regulation of energy metabolism. In this issue, a careful metabolic characterization of mice with genetic deficiency of the GLUT4 glucose transporter in adipocytes and muscle is reported. These mice compensate for decreased peripheral glucose disposal by incr
American Society for Clinical Investigation.
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9. The use of artificial neural networks for the selection of the most appropriate formulation and processing variables in order to predict the in vitro dissolution of sustained release minitablets
The objective of this work was to apply artificial neural networks (ANNs) to examine the relative importance of various factors, both formulation and process, governing the in-vitro dissolution from enteric-coated sustained release (SR) minitablets. Input feature selection (IFS) algorithms were used in order to give an estimate of the relative importance of
Springer-Verlag.