Support Vector Machine

• Introduction
• Installing/Configuring
  • Requirements
  • Installation
• 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 — Predict a value for previously unseen data
  • SVMModel::predict_probability — Return class probabilities for previous unseen data
  • SVMModel::save — Save a model to a file