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SVM-RFE: Selection and visualization of the most relevant features through non-linear kernels

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Support vector machines (SVM) are a powerful tool to analyze data with a number of predictors approximately equal or larger than the number of observations. However, originally, application of SVM to analyze biomedical data was limited because SVM was not designed to evaluate importance of predictor variables.

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Nội dung Text: SVM-RFE: Selection and visualization of the most relevant features through non-linear kernels

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