gov.sandia.cognition.learning.function.categorization
Class MaximumAPosterioriCategorizer.Learner<ObservationType,CategoryType>

java.lang.Object
  extended by gov.sandia.cognition.util.AbstractCloneableSerializable
      extended by gov.sandia.cognition.learning.function.categorization.MaximumAPosterioriCategorizer.Learner<ObservationType,CategoryType>
Type Parameters:
ObservationType - Type of observations
CategoryType - Type of categories
All Implemented Interfaces:
BatchLearner<Collection<? extends InputOutputPair<? extends ObservationType,CategoryType>>,MaximumAPosterioriCategorizer<ObservationType,CategoryType>>, SupervisedBatchLearner<ObservationType,CategoryType,MaximumAPosterioriCategorizer<ObservationType,CategoryType>>, CloneableSerializable, Serializable, Cloneable
Enclosing class:
MaximumAPosterioriCategorizer<ObservationType,CategoryType>

public static class MaximumAPosterioriCategorizer.Learner<ObservationType,CategoryType>
extends AbstractCloneableSerializable
implements SupervisedBatchLearner<ObservationType,CategoryType,MaximumAPosterioriCategorizer<ObservationType,CategoryType>>

Learner for the MAP categorizer

See Also:
Serialized Form

Constructor Summary
MaximumAPosterioriCategorizer.Learner()
          Default constructor
MaximumAPosterioriCategorizer.Learner(BatchLearner<Collection<? extends ObservationType>,? extends ComputableDistribution<ObservationType>> conditionalLearner)
          Creates a new instance of Learner
 
Method Summary
 MaximumAPosterioriCategorizer.Learner<ObservationType,CategoryType> clone()
          This makes public the clone method on the Object class and removes the exception that it throws.
 BatchLearner<Collection<? extends ObservationType>,? extends ComputableDistribution<ObservationType>> getConditionalLearner()
          Getter for conditionalLearner
 MaximumAPosterioriCategorizer<ObservationType,CategoryType> learn(Collection<? extends InputOutputPair<? extends ObservationType,CategoryType>> data)
          The learn method creates an object of ResultType using data of type DataType, using some form of "learning" algorithm.
 void setConditionalLearner(BatchLearner<Collection<? extends ObservationType>,? extends ComputableDistribution<ObservationType>> conditionalLearner)
          Setter for conditionalLearner
 
Methods inherited from class java.lang.Object
equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait
 

Constructor Detail

MaximumAPosterioriCategorizer.Learner

public MaximumAPosterioriCategorizer.Learner()
Default constructor


MaximumAPosterioriCategorizer.Learner

public MaximumAPosterioriCategorizer.Learner(BatchLearner<Collection<? extends ObservationType>,? extends ComputableDistribution<ObservationType>> conditionalLearner)
Creates a new instance of Learner

Parameters:
conditionalLearner - Learner that creates the conditional distributions for each category.
Method Detail

clone

public MaximumAPosterioriCategorizer.Learner<ObservationType,CategoryType> clone()
Description copied from class: AbstractCloneableSerializable
This makes public the clone method on the Object class and removes the exception that it throws. Its default behavior is to automatically create a clone of the exact type of object that the clone is called on and to copy all primitives but to keep all references, which means it is a shallow copy. Extensions of this class may want to override this method (but call super.clone() to implement a "smart copy". That is, to target the most common use case for creating a copy of the object. Because of the default behavior being a shallow copy, extending classes only need to handle fields that need to have a deeper copy (or those that need to be reset). Some of the methods in ObjectUtil may be helpful in implementing a custom clone method. Note: The contract of this method is that you must use super.clone() as the basis for your implementation.

Specified by:
clone in interface CloneableSerializable
Overrides:
clone in class AbstractCloneableSerializable
Returns:
A clone of this object.

learn

public MaximumAPosterioriCategorizer<ObservationType,CategoryType> learn(Collection<? extends InputOutputPair<? extends ObservationType,CategoryType>> data)
Description copied from interface: BatchLearner
The learn method creates an object of ResultType using data of type DataType, using some form of "learning" algorithm.

Specified by:
learn in interface BatchLearner<Collection<? extends InputOutputPair<? extends ObservationType,CategoryType>>,MaximumAPosterioriCategorizer<ObservationType,CategoryType>>
Parameters:
data - The data that the learning algorithm will use to create an object of ResultType.
Returns:
The object that is created based on the given data using the learning algorithm.

getConditionalLearner

public BatchLearner<Collection<? extends ObservationType>,? extends ComputableDistribution<ObservationType>> getConditionalLearner()
Getter for conditionalLearner

Returns:
Learner that creates the conditional distributions for each category.

setConditionalLearner

public void setConditionalLearner(BatchLearner<Collection<? extends ObservationType>,? extends ComputableDistribution<ObservationType>> conditionalLearner)
Setter for conditionalLearner

Parameters:
conditionalLearner - Learner that creates the conditional distributions for each category.