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A Design of an Optimized Classifier based on Feature Elimination for Gene Selection
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 Title & Authors
A Design of an Optimized Classifier based on Feature Elimination for Gene Selection
Lee, Byung-Kwan; Park, Seok-Gyu; Tifani, Yusrina;
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This paper proposes an optimized classifier based on feature elimination (OCFE) for gene selection with combining two feature elimination methods, ReliefF and SVM-RFE. ReliefF algorithm is filter feature selection which rank the data by the importance of the data. SVM-RFE algorithm is a wrapper feature selection which wrapped the data and rank the data based on the weight of feature. With combining these two methods we get less error rate average, 0.3016138 for OCFE and 0.3096779 for SVM-RFE. The proposed method also get better accuracy with 70% for OCFE and 69% for SVM-RFE.
Feature elimination method;OCFE;ReliefF;SVM-REF;
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