Using the JDM API - Java Data Mining: Strategy, Standard, and Practice - page 229

Regression-related interfaces

Table 9-17

supervised.regression.RegressionSettings extends supervised.SupervisedSettings

Methods Description

None

supervised.regression.RegressionModel extends supervised.SupervisedModel

Methods Description

getRSquared Returns the proportional reduction in the variability

of the target associated with the predicted target
values.

supervised.regression.RegressionApplySettings extends supervised.ApplySettings

Methods Description

map(
RegressionApplyContent content,
String destPhysAttrName )

Maps the specified generated value for the prediction to
a destination attribute.

supervised.regression.RegressionTestMetricsTask extends supervised.TestMetrics

Methods Description

None

supervised.TestMetricsTask extends task.Task

Methods Description

set/getActualTargetAttrName(String) Used to set/get the attribute name of the actual targets

in the apply output data.

set/getApplyOutputDataName(String) Used to set/get the name of the apply output data.

set/getPredictedTargetAttrName(String) Used to set/get the attribute name of the predicted

targets in the apply output data.

set/getPredictionRankingAttrName(String) Used to set/get the attribute name of the ranking factors

for the predictions in the apply output data.

set/getTestMetricsName(String) Used to set/get the name of the test metrics to be created

as the result of test metrics task.

supervised.RegressionTestMetrics extends supervised.TestMetrics

Methods Description

getMeanAbsoluteError():java.lang.Double Returns the mean absolute error of predictions.

getMeanActualValue():java.lang.Double Returns the mean (i.e., average) actual target value.

getMeanPredictedValue():java.lang.Double Returns the mean predicted target value.