Package org.tribuo.regression.slm
Class TrainTest.SLMOptions
java.lang.Object
org.tribuo.regression.slm.TrainTest.SLMOptions
- All Implemented Interfaces:
com.oracle.labs.mlrg.olcut.config.Options
- Enclosing class:
- TrainTest
public static class TrainTest.SLMOptions
extends Object
implements com.oracle.labs.mlrg.olcut.config.Options
Command line options.
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Field Summary
Modifier and TypeFieldDescriptionChoose the training algorithm (stepwise forward selection or least angle regression).double
Regularisation strength in the Elastic Net.The data loading options.int
Iterations of Elastic Net.double
Ratio between the l1 and l2 penalties in the Elastic Net.int
Set the maximum number of features.Fields inherited from interface com.oracle.labs.mlrg.olcut.config.Options
header
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Constructor Summary
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Method Summary
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Field Details
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general
The data loading options. -
maxNumFeatures
@Option(charName='m', longName="max-features-num", usage="Set the maximum number of features.") public int maxNumFeaturesSet the maximum number of features. -
algorithm
@Option(charName='a', longName="algorithm", usage="Choose the training algorithm (stepwise forward selection or least angle regression).") public TrainTest.SLMType algorithmChoose the training algorithm (stepwise forward selection or least angle regression). -
alpha
@Option(charName='b', longName="alpha", usage="Regularisation strength in the Elastic Net.") public double alphaRegularisation strength in the Elastic Net. -
l1Ratio
@Option(charName='l', longName="l1Ratio", usage="Ratio between the l1 and l2 penalties in the Elastic Net. Must be between 0 and 1.") public double l1RatioRatio between the l1 and l2 penalties in the Elastic Net. Must be between 0 and 1. -
iterations
@Option(longName="iterations", usage="Iterations of Elastic Net.") public int iterationsIterations of Elastic Net.
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Constructor Details
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SLMOptions
public SLMOptions()
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Method Details
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getOptionsDescription
- Specified by:
getOptionsDescription
in interfacecom.oracle.labs.mlrg.olcut.config.Options
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