Discriminant Model Nugget

Discriminant model nuggets represent the equations estimated by Discriminant nodes. They contain all of the information captured by the discriminant model, as well as information about the model structure and performance.

When you run a stream containing a Discriminant model nugget, the node adds two new fields containing the model's prediction and the associated probability. The names of the new fields are derived from the name of the output field being predicted, prefixed with $D- for the predicted category and $DP- for the associated probability. For example, for an output field named colorpref, the new fields would be named $D-colorpref and $DP-colorpref.

Generating a Filter node. The Generate menu allows you to create a new Filter node to pass input fields based on the results of the model.

Predictor Importance

Optionally, a chart that indicates the relative importance of each predictor in estimating the model may also be displayed on the Model tab. Typically you will want to focus your modeling efforts on the predictors that matter most and consider dropping or ignoring those that matter least. Note this chart is only available if Calculate predictor importance is selected on the Analyze tab before generating the model. See the topic Predictor Importance for more information.