Fast Independent Component Analysis Results

Specify the options for an analysis in the Fast Independent Component Analysis Startup Panel, and click the OK button to run the analysis and display the Fast Independent Component Analysis Results dialog box which contains two tabs, Quick and Advanced.

Element Name Element Type Description
Summary box Box The Summary box at the top of the dialog box displays the current ICA model settings and specifications. You can print the displayed information in spreadsheet format by clicking the Summary button (described below).
Summary Button Displays the ICA model settings and specifications in spreadsheet format.
Cancel Button Closes the Results dialog box and return to the Fast Independent Component Analysis Startup Panel to start a new analysis or to run a saved ICA model.
Options Menu See Options Menu for descriptions of the commands on this menu.
By Group Button Displays the By Group specification dialog box.
Code generator Button If your program is licensed to include this feature, you can generate computer code to implement the current model for predicting new observations. When you click this button, a menu is displayed containing the below three commands:
STATISTICA Visual Basic (SVB) Command Select this command to generate a STATISTICA Visual Basic program containing the code implementing the model. This code will be generated in a form compatible with the nodes of STATISTICA Data Miner; however, you can also simply copy/paste the relevant portion of this code to include it in your custom Visual Basic programs. The code will automatically be displayed in the STATISTICA Visual Basic Program Editor window.
C/C++ language Command Select this command to generate code compatible with the C/C++ language. This option is useful if you want to include the information provided by the final model into custom (C/C++) programs. (See also, Using C/C++/C# Code for Deployment.)
PMML script Command This command will generate code in Predictive Model Markup Language (PMML), which is an XML-based language for storing information about fully trained (parameterized) models, and for sharing those models with other applications. STATISTICA and STATISTICA Enterprise Server contain facilities to use this information to compute predicted values or classifications, i.e., to quickly and efficiently deploy models (typically in the context of data mining projects).