Evolutionary support vector machines (ESVMs) are a novel technique that assimilates the learning engine of the state-of-the-art support vector machines (SVMs) but evolves the coefficients of the ...

Taking motivation from Twin Support Vector Machine (TWSVM), Peng (2009) attempted to propose Twin Support Vector Regression (TSVR) where regressor was obtained via solving pair of Quadratic ...

Dr. James McCaffrey from Microsoft Research presents a complete end-to-end demonstration of the linear support vector regression (linear SVR) technique, where the goal is to predict a single numeric ...

In this study, a fuzzy support vector machine is proposed based on geometric algebra named Clifford fuzzy support vector machine for regression (CFSVR). Through fuzzy membership, different input ...

Pull requests help you collaborate on code with other people. As pull requests are created, they’ll appear here in a searchable and filterable list. To get started, you should create a pull request ...

reinforcement-learning random-forest svm naive-bayes linear-regression cnn thompson-sampling xgboost pca logistic-regression apriori lda ann decision-tree nlp-machine-learning k-nn ...

Abstract Support Vector-based learning methods are an important part of Computational Intelligence techniques. Recent efforts have been dealing with the problem of learning from very large datasets.