To train a network on your own data you first have to massage the data into a format that SNNS can understand. Fortunately this is quite easy. SNNS data files have a header component and a data component. The header defines how many patterns the file contains as well as the dimensionality of the input and target vectors. The files are saved as ASCII test. An example is given in figure .
Figure: Pattern file diagram
The header has to conform exactly to the SNNS format, so watch out for extra spaces etc. I found it easiest to copy headers from one of the example pattern files and to edit the numbers. The data component of the pattern file is simply a listing of numbers that represent the activations of the input and output units. For each pattern the number of values has to match the number of input plus thenumber of output units of the network as defined in the header. For clarity you may wish to put comments (lines starting with a hash (#)) between your patterns like shown in figure . They are ignored by SNNS but may be used by some pattern processing tools. The pattern definitions may have 'CR' characters in them.
Note that while the results saved by SNNS use (almost) the same file format as used for the pattern files, the label values defined in the pattern files are not used.