A Novel Chaotic-Logistic Map Optimizer to Enhance the Performance of Support Vector Machine

The paper presents the development of a novel optimizer to enhance the performance of support vector machine (SVM) by optimizing the parameter, called chaoticSVM. The chaotic logistic map is used to optimize the parameters of SVM for enhanced performance. Experiment is conducted in Python by considering linear and non-linear datasets. The results show that the proposed method performs efficiently as compared with the cSVM, vSVM and Twin Support Vector Machine (TWSVM) on linear and non-linear datasets.

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