must refer to a name of a DataField or DerivedField. It can be absent when the model is used inside a Segment of a MiningModel and does not have a real target field in the input data
When Target specifies optype then it overrides the optype attribute in a corresponding MiningField, if it exists. If the target does not specify optype then the MiningField is used as default. And, in turn, if the MiningField does not specify an optype, it is taken from the corresponding DataField. In other words, a MiningField overrides a DataField, and a Target overrides a MiningField.
If a regression model should predict integers, use the attribute castInteger to control how decimal places should be handled.
If min is present, the predicted value will be the value of min if it is smaller than that.
If max is present, the predicted value will be max if it is larger than that.
can be used for simple rescale of the predicted value: First off, the predicted value is multiplied by rescaleFactor.
after that, rescaleConstant is added to the predicted value.
In classification models, TargetValue is required. For regression models, TargetValue is only optional.
If a regression model should predict integers, use the attribute castInteger to control how decimal places should be handled.
must refer to a name of a DataField or DerivedField.
must refer to a name of a DataField or DerivedField. It can be absent when the model is used inside a Segment of a MiningModel and does not have a real target field in the input data
If max is present, the predicted value will be max if it is larger than that.
If min is present, the predicted value will be the value of min if it is smaller than that.
When Target specifies optype then it overrides the optype attribute in a corresponding MiningField, if it exists.
When Target specifies optype then it overrides the optype attribute in a corresponding MiningField, if it exists. If the target does not specify optype then the MiningField is used as default. And, in turn, if the MiningField does not specify an optype, it is taken from the corresponding DataField. In other words, a MiningField overrides a DataField, and a Target overrides a MiningField.
can be used for simple rescale of the predicted value: First off, the predicted value is multiplied by rescaleFactor.
after that, rescaleConstant is added to the predicted value.
In classification models, TargetValue is required.
In classification models, TargetValue is required. For regression models, TargetValue is only optional.
Note that castInteger, min, max, rescaleConstant and rescaleFactor only apply to models of type regression. Furthermore, they must be applied in sequence, which is:
min and max rescaleFactor rescaleConstant castInteger