Method: knn-class-1

Implementation of K nearest neighbour algorithm for classification. K is chosen on the basis of leave-one-out cross-validation on the training set. K can be chosen on bases of zero-one or squared probability loss. It produces guesses for the most likely category as well as a probability distribution. More details are available in the on-line documentation .


Source code for an implementation in C is available as a compressed tar file.


Directory listing of the results available for the knn-class-1 method. Put the desired files in the appropriate methods directory in your delve hierarchy and uncompress them with using the "gunzip *.gz" command and untar them using "tar -xvf knn-class-1.tar".

Contributed by

Michael Revow

Last Updated 5 November 1996
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