SDKNN k-nearest neighbor classifier

    P=SDKNN(DATA,options)

 INPUT
   DATA      training dataset

 OPTIONS
   k         number of neighbors (def: 1)
   proto     number of prototypes to select per class (def: [] = use all samples)
   protosel  prototype selection method (def: 'random')
              'kcentres','random'
   method    method to compute k-NN with k>1 (def: 'kappa')
              'kappa' - outputs per-class distance to k-th neighbor (one/multi class)
              'classfrac' - outputs class fraction between k neighbors (only multi class)
 OUTPUT
   P         pipeline object

 DESCRIPTION
 SDKNN trains a k-NN classifier (by default k=1). One- or multi-class k-NN
 are supported. By default all provided examples are used as
 prototypes. Prototype selection may be performed by setting number of
 desired prototypes using the 'proto' option.

 READ MORE
 http://perclass.com/doc/guide/classifiers.html#sdknn

 SEE ALSO
 SDKMEANS, SDPARZEN

sdknn is referenced in examples:

• kb18: How to protect a trained discriminant against outliers?
• kb16: Visualize the effect of a change of parameters in a trained classifier