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"Hopfield Networks in Relevance and Redundancy Feature Selection Applied to Classification of Biomedical High-Resolution Micro-CT Images"^^ .
"We study filter–based feature selection methods for classification of biomedical images. For feature selection, we use two filters — a relevance filter which measures usefulness of individual features for target prediction, and a redundancy filter, which measures similarity between features. As selection method that combines relevance and redundancy we try out a Hopfield network. We experimentally compare selection methods, running unitary redundancy and relevance filters, against a greedy algorithm with redundancy thresholds [9], the min-redundancy max-relevance integration [8,23,36], and our Hopfield network selection. We conclude that on the whole, Hopfield selection was one of the most successful methods, outperforming min-redundancy max-relevance when\r\nmore features are selected. "^^ .
"2008-07-17" .
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"Springer Heidelberg"^^ .
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"Advances in data mining: medical applications, e-commerce, marketing, and theoretical aspects. LNAI 5077"^^ .
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"Petra"^^ .
"Perner"^^ .
"Petra Perner"^^ .
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"J."^^ .
"Cerquides"^^ .
"J. Cerquides"^^ .
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"M."^^ .
"Lopez"^^ .
"M. Lopez"^^ .
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"B."^^ .
"Auffarth"^^ .
"B. Auffarth"^^ .
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"Hopfield Networks in Relevance and Redundancy Feature Selection Applied to Classification of Biomedical High-Resolution Micro-CT Images (PDF)"^^ .
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"leipzip08.pdf"^^ .
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"Hopfield Networks in Relevance and Redundancy Feature Selection Applied to Classification of Biomedical High-Resolution Micro-CT Images (Image (JPEG))"^^ .
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"preview.jpg"^^ .
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"Hopfield Networks in Relevance and Redundancy Feature Selection Applied to Classification of Biomedical High-Resolution Micro-CT Images (Indexer Terms)"^^ .
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"indexcodes.txt"^^ .
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"HTML Summary of #7061 \n\nHopfield Networks in Relevance and Redundancy Feature Selection Applied to Classification of Biomedical High-Resolution Micro-CT Images\n\n" .
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"Machine Learning" .
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"Statistical Models" .