In PyDAAL there is a method to get the support vectors of a SVM model (model.getSupportVectors()). However, I don't see a way of getting the labels for these vectors.
I see that there is a new update available that introduces a getSupportIndices() method. I might be able to use this to get the labels from the training dataset.
yes you are right, the support indices can be used to get the respective labels
import numpy as np intBlock = BlockDescriptor_Intc() model.getSupportIndices().getBlockOfRows(0, model.getSupportIndices().getNumberOfRows(), readOnly, intBlock) getIndex = intBlock.getArray() model.getSupportIndices().releaseBlockOfRows(intBlock) trainGroundTruth.getBlockOfRows(0, trainGroundTruth.getNumberOfRows(), readOnly, intBlock) getArray = intBlock.getArray() trainGroundTruth.releaseBlockOfRows(intBlock) print(getArray[np.ndarray.flatten(getIndex)])