Optional Parameters

For a listing of optional parameter strings, see Optional parameter strings.

Selecting input fields

It is important to select the appropriate input fields to avoid that the model becomes overtrained.

There might be logical dependencies between the outcome and some of the input fields. This can occur, for example, if you want to predict customer churn. There might be an input field that indicates the development of the revenue with a customer. Typically, if a customer churns, the revenue declines. Therefore there is a close correlation between a negative revenue development and churn. However, if the decline occurs after the churn, this column is not an appropriate indicator for churn. Therefore this field must be removed from the set of input fields.

For more information about removing one field from the input data, see Removing fields from the input table.

Selecting regression algorithms

Intelligent Miner® provides the following regression algorithms:

• Linear Regression
• Polynomial Regression
• Radial Basis Function (RBF) Regression
• Transform Regression

By default, the Easy Mining procedures use Transform Regression.

You can override the default algorithm for the BuildRegModel procedure and the BuildRegView procedures by using the following option strings with the DM_setAlgorithm option:

Linear Regression

'DM_setAlgorthm(''linear'')'

Polynomial Regression

'DM_setAlgorithm(''Polynomial'')'

RBF Regression

'DM_setAlgorithm(''RBF'')'

Complete Procedure call

For example, you might want to use the Linear Regression algorithm to build a Regression model. The procedure call looks like this:

db2  ''call IDMMX.BuildRegModel('BANK.AVERAGE_BALANCE_LINREGMODEL', 
                                'BANK.BANKCUSTOMERS', 
                                'AVERAGE_BALANCE', 
                                'DM_setAlgoithm(''linear'')')''