Feature Subset Selection
Mostrando 1-12 de 13 artigos, teses e dissertações.
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1. Maximal Information Coefficient and Support Vector Regression Based Nonlinear Feature Selection and QSAR Modeling on Toxicity of Alcohol Compounds to Tadpoles of Rana temporaria
Efficient evaluation of biotoxicity of organics is of vital significance to resource utilization and environmental protection. In this study, toxicity of 110 alcohol compounds to tadpoles of Rana temporaria is adopted as the dependent variable and 1388 physiochemical parameters (features) calculated by PCLIENT are used for representing each compound. A featu
J. Braz. Chem. Soc.. Publicado em: 2019-02
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2. Classification of soil respiration in areas of sugarcane renewal using decision tree
ABSTRACT: The use of data mining is a promising alternative to predict soil respiration from correlated variables. Our objective was to build a model using variable selection and decision tree induction to predict different levels of soil respiration, taking into account physical, chemical and microbiological variables of soil as well as precipitation in ren
Sci. agric. (Piracicaba, Braz.). Publicado em: 2018-05
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3. SeleÃÃo local de caracterÃsticas em agrupamento hierÃrquico de documentos
Hierarchical clustering of documents is used to provide interface for navigating through collections of documents, assisting in the activity of information retrieval. As the vectors representing the documents have a high dimensionality, the presence of irrelevant terms can harm the clustering algorithm. The use of feature selection in text clustering is able
Publicado em: 2009
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4. Uma nova metodologia para seleção de atributos no processo de extração de conhecimento de base de dados baseada na Teoria de Rough Sets
In this dissertation, a new Feature Selection Subsets methodology is proposed, to be used in the Knowledge Discover in Database process. The databases, dimensioned for specific purposes, own in its essence, the intrinsic knowledge to the system of its application. This knowledge is very valuable and important to take strategical decisions in this system. Thu
Publicado em: 2008
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5. 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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6. Classificação de regiões usando atributos de forma e seleção de atributos / Classification of region using shape feature and feature selection
With the steady increase in the number of features available from remote sensing sources, there is a growing necessity to reduce the complexity of the classification task. When data dimensionality is very high, a search strategy should be used to select the subset of features that gives the minimum classification error, considering the limited size of traini
IBICT - Instituto Brasileiro de Informação em Ciência e Tecnologia. Publicado em: 01/04/2005
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7. Classification of region using shape feature and feature selection / Classificação de regiões usando atributos de forma e seleção de atributos
With the steady increase in the number of features available from remote sensing sources, there is a growing necessity to reduce the complexity of the classification task. When data dimensionality is very high, a search strategy should be used to select the subset of features that gives the minimum classification error, considering the limited size of traini
Publicado em: 2005
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8. 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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9. Dimensionality reduction using mean conditional entropy applied for bioinformatics and image processing problems / "Redução de dimensionalidade utilizando entropia condicional média aplicada a problemas de bioinformática e de processamento de imagens"
Dimensionality reduction is a very important pattern recognition problem with many applications. Among the dimensionality reduction techniques, feature selection was the main focus of this research. In general, most dimensionality reduction methods that may be found in the literature privilegiate cases in which the data is linearly separable and with only tw
Publicado em: 2004
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10. Seleção de atributos relevantes para aprendizado de máquina utilizando a abordagem de Rough Sets. / Machine learning feature subset selection using Rough Sets approach.
No Aprendizado de Máquina Supervisionado---AM---o algoritmo de indução trabalha com um conjunto de exemplos de treinamento, no qual cada exemplo é constituído de um vetor com os valores dos atributos e as classes, e tem como tarefa induzir um classificador capaz de predizer a qual classe pertence um novo exemplo. Em geral, os algoritmos de indução bas
Publicado em: 2001
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11. New feature subset selection procedures for classification of expression profiles
BioMed Central.
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12. Biomarker Identification by Feature Wrappers
Gene expression studies bridge the gap between DNA information and trait information by dissecting biochemical pathways into intermediate components between genotype and phenotype. These studies open new avenues for identifying complex disease genes and biomarkers for disease diagnosis and for assessing drug efficacy and toxicity. However, the majority of an
Cold Spring Harbor Laboratory Press.