Daniel@0: Daniel@0: Daniel@0: Daniel@0: Netlab Reference Manual knn Daniel@0: Daniel@0: Daniel@0: Daniel@0:

knn Daniel@0:

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Daniel@0: Purpose Daniel@0:

Daniel@0: Creates a K-nearest-neighbour classifier. Daniel@0: Daniel@0:

Daniel@0: Synopsis Daniel@0:

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Daniel@0: 
Daniel@0: net = knn(nin, nout, k, tr_in, tr_targets)
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Daniel@0: Description Daniel@0:

Daniel@0: net = knn(nin, nout, k, tr_in, tr_targets) creates a KNN model net Daniel@0: with input dimension nin, output dimension nout and k Daniel@0: neighbours. The training data is also stored in the data structure and the Daniel@0: targets are assumed to be using a 1-of-N coding. Daniel@0: Daniel@0:

The fields in net are Daniel@0:

Daniel@0: 
Daniel@0:   type = 'knn'
Daniel@0:   nin = number of inputs
Daniel@0:   nout = number of outputs
Daniel@0:   tr_in = training input data
Daniel@0:   tr_targets = training target data
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Daniel@0: See Also Daniel@0:

Daniel@0: kmeans, knnfwd

Daniel@0: Pages: Daniel@0: Index Daniel@0:

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