Operator PredictionWithDecisionTree

A Feature Construction operator. A Decision Tree is learned using ThePredictingAttributes as learning attributes and TheTargetAttribute as label. TheOutputAttribute contains the labels that the decision tree predicts. The operator may be used to compare predicted and actual values, or in combination with the operator AssignPredictedValueCategorial. All ThePredictingAttributes must belong to TheInputConcept. The pruning confidence level is given in PruningConf as a percentage.

### Parameter

Parameter | Object | Type | optional | min_arg | max_arg | looped | Remarks
TheInputConcept | Concept | Input | no | 1 | 1 | no | inherited
TheTargetAttribute | BaseAttribute | Input | no | 1 | 1 | yes | inherited
ThePredictingAttributes | BaseAttribute | Input | no | 1 |  | yes |
SampleSize | Value | Input | no | 1 | 1 | yes | positive integer
TheOutputAttribute | BaseAttribute | Output | no | 1 | 1 | yes | inherited
PruningConf | Value | Input | no | 1 | 1 | yes | between 0 and 100

The Operator PredictionWithDecisionTree is loopable!