Ten Basic Steps...

Win O R S, Radial Basis Function Artificial Neural Network…

Step One: Start Win O R S.   Additionally, open a Microsoft Word document. If this is the first Word document for this assignment, then start Word by use of the Windows Start menu. If you have previously created a Word document then you must open the document by using the following Win O R S menu tree:. Solution.. Open M-S Word document…

Step Two.  Enter variable names along row one.  Enter a one letter variable type, that is -- a V-Type, across row two. For the RBF application, possible entries include: I. And. D.  The RBF application requires one dependent variable, also referred to as the target variable, and at least one independent variable.  We recommend two or more independent variables when applying the Kajiji neural network framework.

Step Three.  Select the menu sequence:. Applications. Learning Methods. Radial Basis Function.  The Radial Basis Function model setup dialog box appears next. Set the input data range.  Choose the left-facing red arrow to roll-up the dialog box.  Highlight all data cells that may be considered for analysis. For example, the range may contain all cells from B-four to A--E five-eighty-five.  The input data is used to both train and validate the neural network.

Step Four. The forecast range is out-of-sample data.  That is, this data is not part of the input range discussed in step three. These are additional observations on the independent variables that, when applied to the trained neural network, can be used to generate a forecast of the target variable. Accept the default input for the Table.

Step Five. Accept the defaults for the ratio between the training and validation pattern.  Accept the default settings for RBF Method, Error minimization rule, and Transfer function.

Step Six.  Click on Execute to solve the model.

Step Seven. The solution results in three new tabs. RBF Parameters, RBF Predicted, and RBF Weights. The analysis centers about the RBF Parameter tab entries.  NOTE: as successive models are solved, the entries are appended to the next available column.

Step Eight.  Continue the analysis.   View diagnostic charts. Choose the menu sequence: Charts. Diagnostics. Radial Basis Function. The list of available diagnostic charts is presented.

Step Nine: If you have completed your analysis, print the results to the attached Word document. then go to step ten. If you have additional exploratory regressions to execute, go back to step two…

Step Ten:  Save, edit, and close all documents and applications.

This completes the ten basic steps for Radial Basis Function Artificial Neural Network…

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