gov.sandia.cognition.learning.function.categorization

Class MaximumAPosterioriCategorizer.Learner<ObservationType,CategoryType>

java.lang.Object

gov.sandia.cognition.util.AbstractCloneableSerializable

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

Type Parameters:

ObservationType - Type of observations

CategoryType - Type of categories

All Implemented Interfaces:

BatchLearner<java.util.Collection<? extends InputOutputPair<? extends ObservationType,CategoryType>>,MaximumAPosterioriCategorizer<ObservationType,CategoryType>>, SupervisedBatchLearner<ObservationType,CategoryType,MaximumAPosterioriCategorizer<ObservationType,CategoryType>>, CloneableSerializable, java.io.Serializable, java.lang.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

Constructors

Constructor and Description
Learner() Default constructor
Learner(BatchLearner<java.util.Collection<? extends ObservationType>,? extends ComputableDistribution<ObservationType>> conditionalLearner) Creates a new instance of Learner

Method Summary

Modifier and Type	Method and Description
MaximumAPosterioriCategorizer.Learner<ObservationType,CategoryType>	clone() This makes public the clone method on the Object class and removes the exception that it throws.
BatchLearner<java.util.Collection<? extends ObservationType>,? extends ComputableDistribution<ObservationType>>	getConditionalLearner() Getter for conditionalLearner
MaximumAPosterioriCategorizer<ObservationType,CategoryType>	learn(java.util.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<java.util.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

Learner

public Learner()

Default constructor

Learner

public Learner(BatchLearner<java.util.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(java.util.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<java.util.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<java.util.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<java.util.Collection<? extends ObservationType>,? extends ComputableDistribution<ObservationType>> conditionalLearner)

Setter for conditionalLearner

Parameters:

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