gov.sandia.cognition.learning.function.categorization

Class DefaultKernelBinaryCategorizer<InputType>

java.lang.Object

gov.sandia.cognition.util.AbstractCloneableSerializable

gov.sandia.cognition.learning.function.categorization.AbstractBinaryCategorizer<InputType>

gov.sandia.cognition.learning.function.categorization.AbstractDiscriminantBinaryCategorizer<InputType>

gov.sandia.cognition.learning.function.categorization.KernelBinaryCategorizer<InputType,DefaultWeightedValue<InputType>>

gov.sandia.cognition.learning.function.categorization.DefaultKernelBinaryCategorizer<InputType>

Type Parameters:

InputType - The input type for the categorizer.

All Implemented Interfaces:

Evaluator<InputType,java.lang.Boolean>, BinaryCategorizer<InputType>, Categorizer<InputType,java.lang.Boolean>, DiscriminantBinaryCategorizer<InputType>, DiscriminantCategorizer<InputType,java.lang.Boolean,java.lang.Double>, ThresholdBinaryCategorizer<InputType>, KernelContainer<InputType>, CloneableSerializable, java.io.Serializable, java.lang.Cloneable

Direct Known Subclasses:

Forgetron.Result

public class DefaultKernelBinaryCategorizer<InputType>
extends KernelBinaryCategorizer<InputType,DefaultWeightedValue<InputType>>

A default implementation of the KernelBinaryCategorizer that uses the standard way of representing the examples (supports) using a DefaultWeightedValue.

Since:

3.2.0

Author:

Justin Basilico

See Also:

Serialized Form

Field Summary

Fields inherited from class gov.sandia.cognition.learning.function.categorization.KernelBinaryCategorizer

bias, DEFAULT_BIAS, examples, kernel

Fields inherited from class gov.sandia.cognition.learning.function.categorization.AbstractBinaryCategorizer

BINARY_CATEGORIES

Constructor Summary

Constructors

Constructor and Description
DefaultKernelBinaryCategorizer() Creates a new DefaultKernelBinaryCategorizer with a null kernel, no examples, and a zero bias.
DefaultKernelBinaryCategorizer(Kernel<? super InputType> kernel) Creates a new DefaultKernelBinaryCategorizer with the given kernel, no examples, and a zero bias.
DefaultKernelBinaryCategorizer(Kernel<? super InputType> kernel, java.util.Collection<DefaultWeightedValue<InputType>> examples, double bias) Creates a new DefaultKernelBinaryCategorizer with the given parameters.

Method Summary

Modifier and Type	Method and Description
void	add(InputType value, double weight) Adds a new example of the given value with the given weight.
DefaultWeightedValue<InputType>	get(int i) Gets the i-th example.
int	getExampleCount() Returns the number of examples (supports) in the categorizer.
DefaultWeightedValue<InputType>	remove(int i) Removes the i-th example.

Methods inherited from class gov.sandia.cognition.learning.function.categorization.KernelBinaryCategorizer

evaluateAsDouble, getBias, getExamples, getKernel, getThreshold, setBias, setExamples, setKernel, setThreshold

Methods inherited from class gov.sandia.cognition.learning.function.categorization.AbstractDiscriminantBinaryCategorizer

evaluate, evaluateWithDiscriminant

Methods inherited from class gov.sandia.cognition.learning.function.categorization.AbstractBinaryCategorizer

getCategories

Methods inherited from class gov.sandia.cognition.util.AbstractCloneableSerializable

clone

Methods inherited from class java.lang.Object

equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

Methods inherited from interface gov.sandia.cognition.learning.function.categorization.DiscriminantCategorizer

evaluateWithDiscriminant

Methods inherited from interface gov.sandia.cognition.learning.function.categorization.Categorizer

getCategories

Methods inherited from interface gov.sandia.cognition.evaluator.Evaluator

evaluate

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

clone

Constructor Detail

DefaultKernelBinaryCategorizer

public DefaultKernelBinaryCategorizer()

Creates a new DefaultKernelBinaryCategorizer with a null kernel, no examples, and a zero bias.

DefaultKernelBinaryCategorizer

public DefaultKernelBinaryCategorizer(Kernel<? super InputType> kernel)

Creates a new DefaultKernelBinaryCategorizer with the given kernel, no examples, and a zero bias.

Parameters:

kernel - The kernel to use.

DefaultKernelBinaryCategorizer

public DefaultKernelBinaryCategorizer(Kernel<? super InputType> kernel,
                                      java.util.Collection<DefaultWeightedValue<InputType>> examples,
                                      double bias)

Creates a new DefaultKernelBinaryCategorizer with the given parameters.

Parameters:

kernel - The kernel to use.

examples - The collection of examples to use.

bias - The bias term.

Method Detail

add

public void add(InputType value,
                double weight)

Adds a new example of the given value with the given weight.

Parameters:

value - The value to add.

weight - The weight for the value.

get

public DefaultWeightedValue<InputType> get(int i)

Gets the i-th example.

Parameters:

i - The 0-based index of the example to get.

Returns:

The example at the i-th position

remove

public DefaultWeightedValue<InputType> remove(int i)

Removes the i-th example. May not be supported by some collection types.

Parameters:

i - The 0-based index of the example to remove.

Returns:

The item that was removed.

getExampleCount

public int getExampleCount()

Returns the number of examples (supports) in the categorizer.

Returns:

The number of examples (supports) in the categorizer.