This second part of “Porting Support Vector Machine Models…” explains the algorithm for prediction of new data by nonlinear support vector machines (SVM) and Gaussian radial basis kernel. Instead of using pseudo-code, the algorithm is low level implemented in R. This low level implementation is easy to translate to C/C++ or any other language. Remind… Continue reading Porting Support Vector Machine Models from R to Another Language – Part 2

# Tag: Support Vector Machines

## Porting Support Vector Machine Models from R to Another Language – Part 1

R is well known for its machine learning capabilities. With the packages caret and kernlab e.g. you can perform multivariate regression with nonlinear support vector machines (SVM) using Gaussian radial basis kernel. After your model is trained you can predict new data using the S4 method predict(). Thereby, modelling and prediction is conducted on a… Continue reading Porting Support Vector Machine Models from R to Another Language – Part 1