Now, let ∆ be a uniform point-mass distribution over the shifted points andλ kNN , the output score of the kNN model.
given this definition of ∆, it is now straightforward to compute the kNN based reliability indicators: Similarly, we define variables for the SVM classifier by considering a document's locality in terms of nearby support vectors from the set of support vectors, V. To determine β i , we define it in terms of the closest support vector in V to d. Let be half the distance to the nearest point in the shift vectors are all rescaled to have the same length.