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A fuzzy based Lagrangian twin parametric-margin support vector machine (FLTPMSVM)
2017 IEEE Symposium Series on Computational Intelligence (SSCI)
In the spirit of twin parametric-margin support vector machine (TPMSVM) and support vector machine based on fuzzy membership values (FSVM), a new method termed as fuzzy based Lagrangian twin parametric-margin support vector machine (FLTPMSVM) is proposed in this paper to reduce the effect of the outliers. In FLTPMSVM, we assign the weights to each data samples on the basis of fuzzy membership values to reduce the effect of outliers. Also, we consider the square of the 2norm of slack variablesdoi:10.1109/ssci.2017.8280964 dblp:conf/ssci/GuptaBP17 fatcat:n2sx7c2irfetroj4woedm4ejga