ObservationType
- Type of observationsCategoryType
- Type of categoriespublic static class MaximumAPosterioriCategorizer.Learner<ObservationType,CategoryType> extends AbstractCloneableSerializable implements SupervisedBatchLearner<ObservationType,CategoryType,MaximumAPosterioriCategorizer<ObservationType,CategoryType>>
Constructor and Description |
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Learner()
Default constructor
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Learner(BatchLearner<java.util.Collection<? extends ObservationType>,? extends ComputableDistribution<ObservationType>> conditionalLearner)
Creates a new instance of Learner
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Modifier and Type | Method and Description |
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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
|
public Learner()
public Learner(BatchLearner<java.util.Collection<? extends ObservationType>,? extends ComputableDistribution<ObservationType>> conditionalLearner)
conditionalLearner
- Learner that creates the conditional distributions for each
category.public MaximumAPosterioriCategorizer.Learner<ObservationType,CategoryType> clone()
AbstractCloneableSerializable
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.clone
in interface CloneableSerializable
clone
in class AbstractCloneableSerializable
public MaximumAPosterioriCategorizer<ObservationType,CategoryType> learn(java.util.Collection<? extends InputOutputPair<? extends ObservationType,CategoryType>> data)
BatchLearner
learn
method creates an object of ResultType
using
data of type DataType
, using some form of "learning" algorithm.learn
in interface BatchLearner<java.util.Collection<? extends InputOutputPair<? extends ObservationType,CategoryType>>,MaximumAPosterioriCategorizer<ObservationType,CategoryType>>
data
- The data that the learning algorithm will use to create an
object of ResultType
.public BatchLearner<java.util.Collection<? extends ObservationType>,? extends ComputableDistribution<ObservationType>> getConditionalLearner()
public void setConditionalLearner(BatchLearner<java.util.Collection<? extends ObservationType>,? extends ComputableDistribution<ObservationType>> conditionalLearner)
conditionalLearner
- Learner that creates the conditional distributions for each
category.