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Currently, there are three categories of methods to assess importance of variables in SVM: filter, wrapper, and embedded methods. The problem with the existing approaches within these three categories is that they are mainly based on SVM with linear kernels. Therefore, the existing methods do not...
$$ \overset{\sim }{v}{(t)}_{1\mathrm{x}r}^q=\left({\boldsymbol{Z}}_t^{\prime }-\frac{1}{n}{\mathbf{1}}_n^{\prime }K\right)\left({\boldsymbol{I}}_n-\frac{1}{n}{\mathbf{1}}_n{\mathbf{1}}_n^{\prime}\right)\overset{\sim }{\boldsymbol{V}} $$ (5) whe...
1 Pseudo-code of the SVM-RFE algorithm using the linear kernel in a model for binary classification kernels. The idea is based on measuring the smallest change in the cost function by assuming no change in the value of the estimated parameters in the optimization problem. Thus, one avoids ...