gov.sandia.cognition.learning.algorithm.perceptron

Interface LinearizableBinaryCategorizerOnlineLearner<InputType>

Type Parameters:

InputType - The input type that kernel learning happens on.

All Superinterfaces:

BatchAndIncrementalLearner<InputOutputPair<? extends InputType,java.lang.Boolean>,DefaultKernelBinaryCategorizer<InputType>>, BatchLearner<java.util.Collection<? extends InputOutputPair<? extends InputType,java.lang.Boolean>>,DefaultKernelBinaryCategorizer<InputType>>, java.lang.Cloneable, CloneableSerializable, IncrementalLearner<InputOutputPair<? extends InputType,java.lang.Boolean>,DefaultKernelBinaryCategorizer<InputType>>, java.io.Serializable, SupervisedBatchAndIncrementalLearner<InputType,java.lang.Boolean,DefaultKernelBinaryCategorizer<InputType>>, SupervisedBatchLearner<InputType,java.lang.Boolean,DefaultKernelBinaryCategorizer<InputType>>, SupervisedIncrementalLearner<InputType,java.lang.Boolean,DefaultKernelBinaryCategorizer<InputType>>

public interface LinearizableBinaryCategorizerOnlineLearner<InputType>
extends SupervisedBatchAndIncrementalLearner<InputType,java.lang.Boolean,DefaultKernelBinaryCategorizer<InputType>>

Interface for an online learner of a kernel binary categorizer that can also be used for learning a linear categorizer. Thus, there are a second set of methods that are similar to the one for the normal learner that are specifically for linear learning. The companion to this class is KernelizableBinaryCategorizerOnlineLearner.

Since:

3.3.0

Author:

Justin Basilico

See Also:

KernelizableBinaryCategorizerOnlineLearner

Method Summary

Modifier and Type	Method and Description
LinearBinaryCategorizer	createInitialLinearLearnedObject(VectorFactory<?> vectorFactory) Creates the initial learned object.
SupervisedIncrementalLearner<Vectorizable,java.lang.Boolean,LinearBinaryCategorizer>	createLinearLearner(VectorFactory<?> vectorFactory) Creates a new linear learner using the standard learning interfaces based on this learner and its parameters.
void	update(LinearBinaryCategorizer target, InputOutputPair<? extends Vectorizable,java.lang.Boolean> data, VectorFactory<?> vectorFactory) Performs a linear incremental update step on the given object using the given supervised data.
void	update(LinearBinaryCategorizer target, java.lang.Iterable<? extends InputOutputPair<? extends Vectorizable,java.lang.Boolean>> data, VectorFactory<?> vectorFactory) Performs a linear incremental update step on the given object using the given supervised data.
void	update(LinearBinaryCategorizer target, Vectorizable input, boolean output, VectorFactory<?> vectorFactory) Performs a linear incremental update step on the given object using the given supervised data.
void	update(LinearBinaryCategorizer target, Vectorizable input, java.lang.Boolean output, VectorFactory<?> vectorFactory) Performs a linear incremental update step on the given object using the given supervised data.

Methods inherited from interface gov.sandia.cognition.learning.algorithm.SupervisedIncrementalLearner

update

Methods inherited from interface gov.sandia.cognition.learning.algorithm.BatchAndIncrementalLearner

learn

Methods inherited from interface gov.sandia.cognition.learning.algorithm.BatchLearner

learn

Methods inherited from interface gov.sandia.cognition.learning.algorithm.IncrementalLearner

createInitialLearnedObject, update, update

Methods inherited from interface gov.sandia.cognition.util.CloneableSerializable

clone

Method Detail

createInitialLinearLearnedObject

LinearBinaryCategorizer createInitialLinearLearnedObject(VectorFactory<?> vectorFactory)

Creates the initial learned object.

Parameters:

vectorFactory - The vector factory to use.

Returns:

A new linear binary categorizer.

update

void update(LinearBinaryCategorizer target,
            java.lang.Iterable<? extends InputOutputPair<? extends Vectorizable,java.lang.Boolean>> data,
            VectorFactory<?> vectorFactory)

Performs a linear incremental update step on the given object using the given supervised data.

Parameters:

target - The target object to update.

data - The supervised training data

vectorFactory - The vector factory to use.

update

void update(LinearBinaryCategorizer target,
            InputOutputPair<? extends Vectorizable,java.lang.Boolean> data,
            VectorFactory<?> vectorFactory)

Performs a linear incremental update step on the given object using the given supervised data.

Parameters:

target - The target object to update.

data - The supervised training data

vectorFactory - The vector factory to use.

update

void update(LinearBinaryCategorizer target,
            Vectorizable input,
            java.lang.Boolean output,
            VectorFactory<?> vectorFactory)

Performs a linear incremental update step on the given object using the given supervised data.

Parameters:

target - The target object to update.

input - The supervised input value.

output - The supervised output value (label).

vectorFactory - The vector factory to use.

update

void update(LinearBinaryCategorizer target,
            Vectorizable input,
            boolean output,
            VectorFactory<?> vectorFactory)

Performs a linear incremental update step on the given object using the given supervised data.

Parameters:

target - The target object to update.

input - The supervised input value.

output - The supervised output value (label).

vectorFactory - The vector factory to use.

createLinearLearner

SupervisedIncrementalLearner<Vectorizable,java.lang.Boolean,LinearBinaryCategorizer> createLinearLearner(VectorFactory<?> vectorFactory)

Creates a new linear learner using the standard learning interfaces based on this learner and its parameters.

Parameters:

vectorFactory - The vector factory to use.

Returns:

A linear version of this learning algorithm.