Specifying Values for Attributes Importance

Specify the following values for Attribute Importance:

• Target: The value for which to find important attributes. Usually the target of a classification problem.

• Importance Cutoff: A number between 0 and 1.0. This value identifies the smallest value for importance that you want to accept. If the importance of an attribute is a negative number, then that attribute is not correlated with the target, so the cutoff should be nonnegative. The default cutoff is 0. The rank or importance of an attribute enables you to select the attribute to be used in building models.

• Top N: The maximum number of attributes. The default is 100.

• Select a Sample technique for the Attribute Importance calculation. The default is system determined. You can also select Stratified or Random.

  • The system determined technique has a stratified cutoff value with a default of 10.

    • If the distinct count of the selected column is greater than the cutoff value, then use random sampling.

    • If the distinct count of the selected column is less than or equal to the cutoff value, then use stratified sampling

Certain combinations of target and sampling may result in performance problems. You are given a warning if there is a performance problem.