/** * Updates the classifier with the given instance. * * @param instance the new training instance to include in the model * @exception Exception if the instance could not be incorporated in the * model. */ @Override public void updateClassifier(Instance instance) throws Exception { updateClassifier(instance, true); }
/** * Updates the classifier with the given instance. * * @param instance the new training instance to include in the model * @exception Exception if the instance could not be incorporated in the * model. */ @Override public void updateClassifier(Instance instance) throws Exception { updateClassifier(instance, true); }
private void train(Instances data) throws Exception { for (int e = 0; e < m_epochs; e++) { for (int i = 0; i < data.numInstances(); i++) { updateClassifier(data.instance(i), false); } } }
private void train(Instances data) throws Exception { for (int e = 0; e < m_epochs; e++) { for (int i = 0; i < data.numInstances(); i++) { updateClassifier(data.instance(i), false); } } }
DenseInstance metaI = new DenseInstance(instance.weight(), vals); metaI.setDataset(m_fitLogisticStructure); m_svmProbs.updateClassifier(metaI);
DenseInstance metaI = new DenseInstance(instance.weight(), vals); metaI.setDataset(m_fitLogisticStructure); m_svmProbs.updateClassifier(metaI);