gov.sandia.cognition.learning.algorithm.tree
Interface DeciderLearner<InputType,OutputType,CategoryType,DeciderType extends Categorizer<? super InputType,? extends CategoryType>>

Type Parameters:
InputType - The input type to learn a decision for.
OutputType - The output type to learn a decision for.
CategoryType - The category type that the decider will output.
DeciderType - The type of the decision function being learned.
All Superinterfaces:
BatchLearner<Collection<? extends InputOutputPair<? extends InputType,OutputType>>,DeciderType>, Cloneable, CloneableSerializable, Serializable
All Known Subinterfaces:
VectorThresholdMaximumGainLearner<OutputType>
All Known Implementing Classes:
AbstractVectorThresholdMaximumGainLearner, RandomSubVectorThresholdLearner, VectorThresholdGiniImpurityLearner, VectorThresholdHellingerDistanceLearner, VectorThresholdInformationGainLearner, VectorThresholdVarianceLearner

public interface DeciderLearner<InputType,OutputType,CategoryType,DeciderType extends Categorizer<? super InputType,? extends CategoryType>>
extends BatchLearner<Collection<? extends InputOutputPair<? extends InputType,OutputType>>,DeciderType>

The DeciderLearner interface defines the functionality of a learner that can be used to learn a decision function inside a decision tree.

Since:
2.0
Author:
Justin Basilico

Method Summary
 
Methods inherited from interface gov.sandia.cognition.learning.algorithm.BatchLearner
learn
 
Methods inherited from interface gov.sandia.cognition.util.CloneableSerializable
clone