Support Vector Machine

Introduction
Installing/Configuring
Examples
SVM — The SVM class
- SVM::__construct — Construct a new SVM object
- SVM::crossvalidate — Test training params on subsets of the training data
- SVM::getOptions — Return the current training parameters
- SVM::setOptions — Set training parameters
- SVM::train — Create a SVMModel based on training data
SVMModel — The SVMModel class
- SVMModel::checkProbabilityModel — Returns true if the model has probability information
- SVMModel::__construct — Construct a new SVMModel
- SVMModel::getLabels — Get the labels the model was trained on
- SVMModel::getNrClass — Returns the number of classes the model was trained with
- SVMModel::getSvmType — Get the SVM type the model was trained with
- SVMModel::getSvrProbability — Get the sigma value for regression types
- SVMModel::load — Load a saved SVM Model
- SVMModel::predict_probability — Return class probabilities for previous unseen data
- SVMModel::predict — Predict a value for previously unseen data
- SVMModel::save — Save a model to a file