Competitive layer
competlayer(numClasses,kohonenLR,conscienceLR)
Competitive layers learn to classify input vectors into a given number of classes, according to similarity between vectors, with a preference for equal numbers of vectors per class.
competlayer(numClasses,kohonenLR,conscienceLR)
takes these arguments,
numClasses | Number of classes to classify inputs (default = 5) |
kohonenLR | Learning rate for Kohonen weights (default = 0.01) |
conscienceLR | Learning rate for conscience bias (default = 0.001) |
and returns a competitive layer with numClasses
neurons.
Here a competitive layer is trained to classify 150 iris flowers into 6 classes.
inputs = iris_dataset; net = competlayer(6); net = train(net,inputs); view(net) outputs = net(inputs); classes = vec2ind(outputs);