BNW using Octave instead of Matlab.

This version of BNW should perform the same as the original version. The only difference is that it uses Octave instead of Matlab when running BayesNet Toolbox during parameter learning.

I am calling this BNW_1.02. It can be accessed at:
compbio.uthsc.edu/BNW_1.02

1 files changed, 34 insertions, 0 deletions

diff --git a/sourcecodes/bnt-master/netlab3.3/knn.m b/sourcecodes/bnt-master/netlab3.3/knn.m
new file mode 100644
index 00000000..2a171804
--- /dev/null
+++ b/sourcecodes/bnt-master/netlab3.3/knn.m
@@ -0,0 +1,34 @@
+function net = knn(nin, nout, k, tr_in, tr_targets)
+%KNN	Creates a K-nearest-neighbour classifier.
+%
+%	Description
+%	NET = KNN(NIN, NOUT, K, TR_IN, TR_TARGETS) creates a KNN model NET
+%	with input dimension NIN, output dimension NOUT and K neighbours.
+%	The training data is also stored in the data structure and the
+%	targets are assumed to be using a 1-of-N coding.
+%
+%	The fields in NET are
+%	  type = 'knn'
+%	  nin = number of inputs
+%	  nout = number of outputs
+%	  tr_in = training input data
+%	  tr_targets = training target data
+%
+%	See also
+%	KMEANS, KNNFWD
+%
+
+%	Copyright (c) Ian T Nabney (1996-2001)
+
+
+net.type = 'knn';
+net.nin = nin;
+net.nout = nout;
+net.k = k;
+errstring = consist(net, 'knn', tr_in, tr_targets);
+if ~isempty(errstring)
+  error(errstring);
+end
+net.tr_in = tr_in; 
+net.tr_targets = tr_targets;
+