SVM Learner

This node trains a support vector machine on the input data. It supports a number of different kernels (HyperTangent, Polynomial and RBF). The SVM learner supports multiple class problems as well (by computing the hyperplane between each class and the rest), but note that this will increase the runtime.

The SVM learning algorithm used is described in the following papers: Fast Training of Support Vector Machines using Sequential Minimal Optimization , by John C. Platt and Improvements to Platt's SMO Algorithm for SVM Classifier Design , by S. S. Keerthi et. al.

Input ports

1. Type: Table
   Training Data
   Datatable with training data

Output ports

1. Type: PMML
   Trained SVM
   Trained Support Vector Machine