Emphatic Constraints Support Vector Machine
Mostafa Sabzekar, Hadi Sadoghi Yazdi, Mahmoud Naghibzadeh, Sohrab Effati · International Journal of Computer and Electrical Engineering · 2010
In this paper, a new support vector machine, ESVM, with more emphasis on constraints is presented.The constraints are fuzzy inequalities.With this scheme, two problems are solved: training samples with some degree of uncertainty, and samples with tolerance.Also, the fuzzy SVM (FSVM) model is modified with emphasis constraints.The new model is called fuzzy ESVM (FESVM), in this paper.With this scheme we will able to consider importance degree for samples both in the cost function and constraints, simultaneously.Necessary experiments are performed and the results show the superiority of the proposed methods.ESVM and fuzzy ESVM are strongly recommended to the researchers who work on data sets with noisy or low degree of certainty samples.