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Metalearning for gene expression data classification

Title
Metalearning for gene expression data classification
Type
Chapter or Part of a Book
Year
2008
Authors
De Souza, BF
(Author)
Other
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De Carvalho, A
(Author)
Other
The person does not belong to the institution. The person does not belong to the institution. The person does not belong to the institution. Without AUTHENTICUS Without ORCID
Soares, C
(Author)
FEP
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Other information
Authenticus ID: P-007-NTG
Abstract (EN): Machine Learning techniques have been largely applied to the problem of class prediction in microarray data. Nevertheless, current approaches to select appropriate methods for such task often result unsatisfactory in many ways, instigating the need for the development of tools to automate the process. In this context, the authors introduce the use of metalearning in the specific domain of gene expression classification. Experiments with the KNN-ranking method for algorithm recommendation applied for 49 datasets yielded successful results. © 2008 IEEE.
Language: English
Type (Professor's evaluation): Scientific
Notes: 8Th International Conference on Hybrid Intelligent Systems, His 2008, 10 September 2008 through 12 September 2008, Sponsors IEEE Systems Man and Cybernetics Society;European Neural Network Society;International Fuzzy Systems Association;European Society for Fuzzy Logic and Technology
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Chapter or Part of a Book
Rossi, ALD; Carvalho, ACPLF; Soares, C
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