SANN - Custom Neural Network

Select the Custom Neural Networks (CNN) option button on the Quick tab of the SANN - Data selection dialog box, and click OK to display the SANN - Custom Neural Network dialog box. Depending on the analysis type selected in the Startup Panel (and in some cases, the selected network type), this dialog box can contain up to four tabs. The available tabs are: Quick (MLP/RBF), MLP, RBF, Decay (MLP/RBF), Quick (Kohonen), and Kohonen Training. Use the options on these tabs to configure the custom neural networks.

Active neural networks. The grid in the Active neural networks group box provides a quick view of the networks you have created for modeling your data. If you have not trained any networks or if you have not selected any active networks, this grid will be empty.

Train. Click the Train button to build (train) networks according to the specifications made on the tabs of this dialog box. While the networks are being trained, the Neural networks training in progress dialog box will be displayed. This dialog box provides summary details of networks as they are created. When the requested number of networks has been trained, the SANN - Results dialog box is displayed.

Go to results. Click this button to display the Results dialog box without performing additional training. Note that if the Active neural networks grid is empty, this button will not be available.

Save networks. Click this button to display a drop-down list containing the following commands:

PMML script. Select PMML script to display the Save PMML file dialog box, which contains options to store the active networks for future use. Note that this dialog will be displayed only when the Active neural networks grid contains networks. Stored PMML networks can be opened by clicking the Load network files button in the SANN - New Analysis/Deployment Startup Panel.

C/C++ language. Select C/C++ language to display the Save C file dialog box, which contains options to store the active networks for future use.

C#. Select this command to generate code as C#.

Java. Click this command to generate code in Java script.

SAS code. Select SAS code to display the Save SAS file dialog box, which contains options to save deployment code for the created model as SAS code (a .sas file). See also, Rules for SAS Variable Names.

SQL stored procedure in C#. Click this command to generate code as a C# class intended for use in a SQL Server user defined function.

SQL User Defined Function in C#. Select this command to generate code as a C# class intended for use as a SQL Server user defined function.

Teradata. Select this command to generate code as C Computer language function intended for use as a user defined function in a TeraData querying environment.

Deployment to STATISTICA Enterprise. Select this command to deploy the results as an Analysis Configuration in STATISTICA Enterprise. Note that appropriately formatted data must be available in a STATISTICA Enterprise Data Configuration before the results can be deployed to an Analysis Configuration.

Data statistics. Click the Data statistics button to generate a spreadsheet containing the mean, standard deviation, minimum value and maximum value for each continuous variable in the analysis. These data statistics will be broken down by each sample (training, testing, and validation) and also reported for the overall data set.

Summary. Click the Summary button to generate a spreadsheet containing the summary details listed in the Active neural networks grid box. Note that if the Active neural networks grid is empty, this button will not be available.

Cancel. Click the Cancel button to exit the SANN - Custom Neural Network dialog box and return to the SANN - Data selection dialog box. Any selections made will be ignored, and you will be prompted to discard any networks in the Active neural networks grid.

Options. Click the Options button to display the Options menu.