Java Reference
In-Depth Information
24. csApplyTaskFactory.create(
25. customerProfile, "attrition_model", "attritionApplySettings");
26. } else {
27. csRecordApplyTask.setInputRecord(customerProfile);
28. }
29. dmeConn.execute(csRecordApplyTask, timeOut);
30. PhysicalDataRecord outputRecord = csRecordApplyTask.getOutputRecord();
31. return ((Number)outputRecord.getValue("Probability")).doubleValue();
32. }
Using Regression Interfaces
The javax.datamining.supervised.regression package contains regression
function interfaces, such as RegressionSettings , RegressionModel ,
RegressionApplySettings , RegressionTestMetrics , etc. Regression inter-
faces are similar to classification interfaces in many ways. The main
difference, however, is that regression predicts continuous values,
whereas classification predicts discrete values. Hence, regression
does not accept objects for cost matrix, target category set, or prior
probabilities. All JDM-specified algorithms discussed for the classifi-
cation can also be used for regression. However, in the case of the
support vector machine (SVM) algorithm, due to variations between
regression and classification JDM explicitly defines an algorithm set-
tings interface called SVMRegressionSettings . This section illustrates the
use of the regression-related interfaces by taking the prediction of the
real-estate appraisal value example that was discussed in Section 7.2.
Table 9-17 lists all the regression-specific interface method details.
Note that RegressionSettings doesn't have any regression-specific
build settings. Even though there are no regression-specific settings,
this interface is defined to be consistent with other build settings for
future extensions. These setting do, however, inform the BuildTask
object to build a regression model when executed. A RegressionModel
object can return the R-squared error if the regression model validates
the model either on the build data itself or using the validate data
specified at build time. The RegressionApplySettings has only one map
method through which a user can specify the desired apply content
in the apply output table. The RegressionApplyContent allows users to
specify content for the predicted value and the prediction confidence .
The RegressionTestMetrics interface defines the get methods for
various types of regression error measures that were discussed in
Section 7.2.5. By extending the generic supervised.TestMetricsTask , the
RegressionTestMetricsTask computes test metrics using an apply out-
put table instead of a regression model.
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