How to the coding should be for a neural pattern recognition & classification of 3 input and 1 binary output?

I am doing a study on Neural Pattern Recognition and Classification. My idea is, with 3 numerical entry as input, the Neuron Network function will classify these entries with a binary output of either 1 or 0. Please, can someone guide me with the MATLAB coding?

Answer 1

[Greg Heath]

Typically, c-class Classifiers of I-dimensional inputs are trained with input and target matrix sizes

 [I N ] = size(input)
 [c N ] = size(target)

where the target columns are 1/0 c-dimensional unit vectors.

For example, with three distinct classes the targets are the column vectors of the 3-dimensional unit matrix:

 [ 1 0 0 ]
 [ 0 1 0 ]
 [ 0 0 1 ]

Using SOFTMAX as the output function, the outputs will be unit sum non-negative vectors and are interpreted as the a posteriori probabilities of the input belonging to each class.

The classification is determined by the largest a postiori probability:

For example,

   [ 0.70 0.40  0.11
     0.10 0.05  0.66   ===>  [ 1 3 2 ]
     0.20 0.55  0.33]

THE EXCEPTION IS WHEN THERE ARE ONLY 2 CLASSES. Then, only one output in [0 1 ] is necessary. The other output is obtained by subtracting the output from one.

Hope this helps.

 *Thank you for formally accepting my answer*

Greg