KNNM

Trainable K-Nearest Neighbour density estimation

    W = KNNM(A,KNN)
    W = A*KNNM([],KNN)
    W = A*KNNM(KNN)

    D = B*W

Input
A	Dataset used for training
B	Dataset used for evaluation
KNN	Number of nearest neighbours

Output
W	Density estimate

Description

A density estimator is constructed based on the k-Nearest Neighbour rule  using the objects in A. In case A is labeled, density estimates are  performed classwise and combined by the class priors. The default KNN is  the square root of the size of the class. The data is scaled by variance  normalisation determined by the training set.

The mapping W may be applied to a new dataset B using DENSITY = B*W.

See also

datasets, mappings, knnc, parzenm, gaussm,