Package javax.datamining.supervised.regression

This package contains Java classes describing the settings, model, and test task and result for regression mining function.

See:
Description

Interface Summary

RegressionApplySettings	A RegressionApplySettings captures a specification that prescribes the output of an apply task specific to a regression model.
RegressionApplySettingsFactory	A factory class that creates instances of RegressionApplySettings.
RegressionModel	RegressionModel contains the metadata resulting from a model build using an RegressionSettings.
RegressionSettings	A RegressionSettings instance supports function settings specific to the regression mining function.
RegressionSettingsFactory	A factory class that creates instances of RegressionSettings.
RegressionTestMetrics	A RegressionTestResult provides an interface to access the metadata resulting from executing a RegressionTestTask.
RegressionTestMetricsTask	RegressionTestMetricsTask is a mining task used for computing and creating test metrics objects given an apply output data.
RegressionTestMetricsTaskFactory
RegressionTestTask	An RegressionTestTask is a mining task used for testing a RegressionModel to measure the goodness of the model.
RegressionTestTaskFactory	A factory class that creates instances of RegressionTestTask.

Class Summary

RegressionApplyContent	The enumeration RegressionApplyContent designates the types of generated value to appear in the apply output of a regression model.
RegressionCapability	The enumeration RegressionCapability enumerates a list of the capabilities of the regression function being supported in a particular implementation.

Package javax.datamining.supervised.regression Description

This package contains Java classes describing the settings, model, and test task and result for regression mining function. Regression has been used in financial forecasting, time series analysis, biomedical and drug response modeling, and environmental modeling. As a type of supervised learning, regression involves predicting a continuous, numerical values of the target attribute.