A Filter Method for Feature Selection for SELDI-TOF Mass Spectrum

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概要

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• We propose a new filter method for feature selection for SELDI-TOF mass spectrum datasets. In the method, a new relevance index was defined to represent the goodness of a feature by considering the distribution of samples based on the counts. The relevance index can be used to obtain the feature sets for classification. Our method can be applied to mass spectrum datasets with extremely high dimensions and process the clinical datasets with practical sizes in acceptable calculation time since it is based on simple counting of samples. The new method was applied to the three public mass spectrum datasets and showed better or comparable results than conventional filter methods.

• （社）電子情報通信学会の論文
• 2009-02-01

著者

• Vu Trung-nghia

  Department Of Computer Engineering Korea Aerospace University

• OHN Syng-Yup

  Department of Computer Engineering, Korea Aerospace University

• Ohn Syng-yup

  Department Of Computer Engineering Korea Aerospace University

関連論文

• A Filter Method for Feature Selection for SELDI-TOF Mass Spectrum

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