|
Loading the recall file |
In order to recall the network you need to load the recall file, and specify an output file.
To load the training file, press the Open button 
and browse to find the required file.
Alternatively, select Load Recall File from the Recall menu and browse to find the required file.
The file can have any extension, but the convention is for recall files to have the extension *.rcl, and it must be of the required format.
|
Viewing the recall file |
You can press the View button 
to view your recall file, or select View Recall File from the Recall menu.
|
Specifying the output file |
In order to recall the network you also need to specify a file to save the output to.
To specify the output file, press the
Open button and give
the file a name, e.g. iris_recall.out.
Alternatively, select Save Output File from the Recall menu and specify the file.
The file can have any extension, but the
convention is for recall files to have the extension *.out.
|
Recalling the network |
Once the recall file has been loaded and the output file specified, press the Recall button, or select Recall from the Recall menu.
This will save the recall output into the file that has been specified, and it can now be viewed.
|
Viewing the output file |
You can press the View button to view your output file, or select View
Output File from the Recall menu.
Note: You need to associate files of type *.out with a text editor in Windows Explorer in order to view the files through the FuzzyCOPE GUI.
Below is an example output generated after training of an MLP network.
What you see are the outputs that have been generated by the trained network. You should compare these generated outputs to the desired outputs in the recall file to see how well the network has been trained.
[FormatVersion = 1.0] /* This is a standard version number. Any value larger than 1.0 will not work*/
[DataSet] /*Details of the data set*/
[Rows = 75]
[Inputs = 0]
[ExpectedOutputs = 3]
[GeneratedOutputs = 0]
[Error = 0]
[Data] /*the generated output values for each row of input data*/
0.993998841762934 0.00544656413324473 5.15907219113569e-18 0.995852497899786 0.00342361058926546 4.1905021395423e-18 0.997148819595633 0.00200432439496846 1.50127149577872e-18 0.996993453343725 0.00213744138058091 1.53095629810707e-18 0.995817421149046 0.00330684317212554 3.13005015949153e-18 0.995082866669796 0.00412727302374539 3.93914986389275e-18 0.996142616260044 0.00311228791207475 3.18834061462997e-18
/*... this file would contain more output rows here*/
[~Data]
[~DataSet]