jsat.classifiers.svm

Class SupportVectorLearner

java.lang.Object

jsat.classifiers.svm.SupportVectorLearner

All Implemented Interfaces:

java.io.Serializable

Direct Known Subclasses:

CSKLRBatch, DCSVM, LSSVM, PegasosK, PlattSMO, SBP, SVMnoBias

public abstract class SupportVectorLearner
extends java.lang.Object
implements java.io.Serializable

Base class for support vector style learners. This means that the learner performs batch training on a fixed set of training points using a kernel to project the data into a different space. The final set of vectors used may or may not be sparse. It does not necessarily have to be a Support Vector machine.

This class provides caching mechanism to transparently provide faster kernel.

See Also:

Serialized Form

Nested Class Summary

Nested Classes

Modifier and Type	Class and Description
static class	SupportVectorLearner.CacheMode Determines how the final kernel values are cached.

Constructor Summary

Constructors

Constructor and Description
SupportVectorLearner(KernelTrick kernel, SupportVectorLearner.CacheMode cacheMode) Creates a new Support Vector Learner
SupportVectorLearner(SupportVectorLearner toCopy) Copy constructor

Method Summary

Modifier and Type	Method and Description
SupportVectorLearner.CacheMode	getCacheMode() Returns the current caching mode in use
int	getCacheValue() Returns the current cache value
KernelTrick	getKernel()
void	setCacheMode(SupportVectorLearner.CacheMode cacheMode) Calling this sets the method of caching that will be used.
void	setCacheSize(long N, long bytes) Sets the cache value to one that will use the specified amount of memory.
void	setCacheValue(int cacheValue) Sets the cache value, which may be interpreted differently by different caching schemes.
void	setKernel(KernelTrick kernel) Sets the kernel trick to use

Methods inherited from class java.lang.Object

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

Constructor Detail

SupportVectorLearner

public SupportVectorLearner(KernelTrick kernel,
                            SupportVectorLearner.CacheMode cacheMode)

Creates a new Support Vector Learner

Parameters:

kernel - the kernel trick to use

cacheMode - the kernel caching method to use

SupportVectorLearner

public SupportVectorLearner(SupportVectorLearner toCopy)

Copy constructor

Parameters:

toCopy - the object to copy

Method Detail

setKernel

public void setKernel(KernelTrick kernel)

Sets the kernel trick to use

Parameters:

kernel - the kernel trick to use

setCacheValue

public void setCacheValue(int cacheValue)

Sets the cache value, which may be interpreted differently by different caching schemes.
This is currently only used for SupportVectorLearner.CacheMode.ROWS, where the value indicates how many rows will be cached.

Parameters:

cacheValue - the cache value to be used

setCacheSize

public void setCacheSize(long N,
                         long bytes)

Sets the cache value to one that will use the specified amount of memory. If the amount of memory specified is great enough, this method will automatically set the cache mode to SupportVectorLearner.CacheMode.FULL.

Parameters:

N - the number of data points

bytes - the number of bytes of memory to make the cache

getCacheValue

public int getCacheValue()

Returns the current cache value

Returns:

the current cache value

getCacheMode

public SupportVectorLearner.CacheMode getCacheMode()

Returns the current caching mode in use

Returns:

the current caching mode in use

setCacheMode

public void setCacheMode(SupportVectorLearner.CacheMode cacheMode)

Calling this sets the method of caching that will be used.
This is called called by the implementing class to initialize and clear the caches. Calling this with the current cache mode will initialize the caches. Once training is complete, call again with null to deinitialize the caches.

Parameters:

cacheMode -

getKernel

public KernelTrick getKernel()