how to apply DATA to inputs in neural network MLP?

hello, i want to create a network but i don't know how to apply my data.my data is 64 person that 15 people have park , 20 hunt ,13 als and 16 control. each one has 13 feature and about 300 row (not all of them exactly the same).i want to input my data for training. the output of this data is 4 neuron (als, hunt,park,cont). the network should diagnose this 4. how should i apply this input in MLP? i will be appriciate if any one can help me. ps, i attached each of my data not all of them.

[Walter Roberson]

What do the rows represent? How do you know the boundary between one person and the next in the data?

I gather you are looking at Parkinson's, Huntington's, Amyotrophic Lateral Sclerosis, and controls.

[helia mb]

the row data is time. and all of this attach file is for one person having that disease. i got my data from here you can look if you want http://www.physionet.org/physiobank/database/gaitndd/?M=A

Answer 1

[Greg Heath]

Data must consist of N pairs:

 I-dimensional "I"nputs in an I x N matrix

and a corresponding

 O x N "O"utput target matrix with O-dimensional columns

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

For a simple classification example use the commands

 help patternnet
 doc patternnet

for more extensive examples search BOTH NEWSGROUP and ANSWERS with

 greg patternnet tutorial

and

 greg patternnet

Hope this helps,

Thank you for formally accepting my answer

Greg

[helia mb]

i really appreciate for answering me but i need some one to told me exactly what should i do. what ever thank you.