Use this module to process a data file through a trained neural network to produce the network's classifications or predictions for each pattern in the file. A file of outputs (the .OUT file) is produced.
If you include actual values in the file, all modules except Kohonen give you check boxes to include actual values and/or the differences between the actual answer's and the network's answers in the .OUT file. If there is more than one output, the actual values and differences will be displayed for each output. The order of display is actual values, followed by predicted values, followed by differences.
If your data file includes an * in a cell beneath a column labeled A (Actual output), the * will be replaced with a 0 and a prediction will be made in that row when you apply a network. A prediction will not be made in a row if your data file includes an * in a cell beneath a column labeled I (Input). (The column labels were specified in the Define Inputs/Outputs module.) Previous releases of NeuroShell 2 up to Release 2.0 would not apply a trained network to a data row if it contained an * in either an A or I column.
Use the Run Menu to start processing the data file through the network. Also use this menu to interrupt processing.
Use the File Menu to select an alternate pattern file, view the pattern file, view the output, or copy the results (the statistics computed when the network is applied) to the Windows clipboard. If an alternate file is selected, the file must have the same prefix (problem name) and must be in the same directory as the .MMX (created in the Define Inputs and Outputs module) and the .FIG file (created in the Design module).
For more details on specific network types, see:
Apply Backpropagation Network
Apply Kohonen Network
Apply PNN Network
Apply GRNN Network
Apply GMDH Network
File Note: This module defaults to processing the .PAT file, but you can apply the network to any file that is in the NeuroShell 2 file format (the same as Lotus 1-2-3 .WK1 file format) simply by using the File Menu to select a file. The inputs must be in the same columns in the same order as the .PAT file with which the network was trained. This module places the network's classifications or predictions into an .OUT file.
This module will run as an independent program.