Feature Selection with the logRatio Kernel
نویسندگان
چکیده
In this article we present a novel kernel function, logRatio, which was designed to address two common problems in biological applications: data preprocessing and attribute interaction modelling. An extension of the SVMRFE feature selection algorithm was built around this new kernel function and compared with the original on a number of biological data and text classification problems. Experiments showed that SVMRFE based on the logRatio kernel detects relevant information and handles attribute redundancy more effectively than SVMRFE coupled with other kernels.
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