org.apache.mahout.classifier.sgd
Class AdaptiveLogisticRegression.Wrapper

java.lang.Object
  extended by org.apache.mahout.classifier.sgd.AdaptiveLogisticRegression.Wrapper
All Implemented Interfaces:
Payload<AdaptiveLogisticRegression.Wrapper>
Enclosing class:
AdaptiveLogisticRegression

public static class AdaptiveLogisticRegression.Wrapper
extends java.lang.Object
implements Payload<AdaptiveLogisticRegression.Wrapper>

Provides a shim between the EP optimization stuff and the CrossFoldLearner. The most important interface has to do with the parameters of the optimization. These are taken from the double[] params in the following order

. All other parameters are set in such a way so as to defeat annealing to the extent possible. This lets the evolutionary algorithm handle the annealing.

Note that per coefficient annealing is still done and no optimization of the per coefficient offset is done.


Constructor Summary
AdaptiveLogisticRegression.Wrapper(int numCategories, int numFeatures, PriorFunction prior)
           
 
Method Summary
 AdaptiveLogisticRegression.Wrapper copy()
           
 void freeze(State<AdaptiveLogisticRegression.Wrapper> s)
           
 CrossFoldLearner getLearner()
           
 void setAucEvaluator(OnlineAuc auc)
           
 void setMappings(State<AdaptiveLogisticRegression.Wrapper> x)
           
 java.lang.String toString()
           
 void train(AdaptiveLogisticRegression.TrainingExample example)
           
 void update(double[] params)
           
 
Methods inherited from class java.lang.Object
clone, equals, finalize, getClass, hashCode, notify, notifyAll, wait, wait, wait
 

Constructor Detail

AdaptiveLogisticRegression.Wrapper

public AdaptiveLogisticRegression.Wrapper(int numCategories,
                                          int numFeatures,
                                          PriorFunction prior)
Method Detail

copy

public AdaptiveLogisticRegression.Wrapper copy()
Specified by:
copy in interface Payload<AdaptiveLogisticRegression.Wrapper>

update

public void update(double[] params)
Specified by:
update in interface Payload<AdaptiveLogisticRegression.Wrapper>

freeze

public void freeze(State<AdaptiveLogisticRegression.Wrapper> s)

setMappings

public void setMappings(State<AdaptiveLogisticRegression.Wrapper> x)

train

public void train(AdaptiveLogisticRegression.TrainingExample example)

getLearner

public CrossFoldLearner getLearner()

toString

public java.lang.String toString()
Overrides:
toString in class java.lang.Object

setAucEvaluator

public void setAucEvaluator(OnlineAuc auc)


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