Package | Description |
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de.jstacs.classifiers |
This package provides the framework for any classifier.
|
de.jstacs.classifiers.differentiableSequenceScoreBased |
Provides the classes for
Classifier s that are based on SequenceScore s.It includes a sub-package for discriminative objective functions, namely conditional likelihood and supervised posterior, and a separate sub-package for the parameter priors, that can be used for the supervised posterior. |
de.jstacs.classifiers.differentiableSequenceScoreBased.gendismix |
Provides an implementation of a classifier that allows to train the parameters of a set of
DifferentiableStatisticalModel s by
a unified generative-discriminative learning principle. |
de.jstacs.classifiers.differentiableSequenceScoreBased.msp |
Provides an implementation of a classifier that allows to train the parameters of a set of
DifferentiableStatisticalModel s either
by maximum supervised posterior (MSP) or by maximum conditional likelihood (MCL). |
de.jstacs.classifiers.differentiableSequenceScoreBased.sampling |
Provides the classes for
AbstractScoreBasedClassifier s that are based on
SamplingDifferentiableStatisticalModel s
and that sample parameters using the Metropolis-Hastings algorithm. |
de.jstacs.classifiers.trainSMBased |
Provides the classes for
Classifier s that are based on TrainableStatisticalModel s. |
de.jstacs.classifiers.utils |
Provides some useful classes for working with classifiers.
|
de.jstacs.sequenceScores.statisticalModels.trainable.discrete.inhomogeneous.shared |
Modifier and Type | Class and Description |
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class |
MappingClassifier
This class allows the user to train the classifier on a given number of
classes and to evaluate the classifier on a smaller number of classes by
mapping classes together.
|
Modifier and Type | Method and Description |
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AbstractScoreBasedClassifier |
AbstractScoreBasedClassifier.clone() |
Constructor and Description |
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MappingClassifier(AbstractScoreBasedClassifier classifier,
int... mapping)
Creates a new
MappingClassifier from a given classifier and a
class mapping. |
Modifier and Type | Class and Description |
---|---|
class |
ScoreClassifier
This abstract class implements the main functionality of a
DifferentiableSequenceScore based classifier. |
Modifier and Type | Class and Description |
---|---|
class |
GenDisMixClassifier
This class implements a classifier the optimizes the following function
![]() |
Modifier and Type | Class and Description |
---|---|
class |
MSPClassifier
This class implements a classifier that allows the training via MCL or MSP principle.
|
Modifier and Type | Class and Description |
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class |
SamplingGenDisMixClassifier
A classifier that samples its parameters from a
LogGenDisMixFunction using the
Metropolis-Hastings algorithm. |
class |
SamplingScoreBasedClassifier
A classifier that samples the parameters of
SamplingDifferentiableStatisticalModel s by the Metropolis-Hastings algorithm. |
Modifier and Type | Class and Description |
---|---|
class |
TrainSMBasedClassifier
Classifier that works on
TrainableStatisticalModel s for each of the different classes. |
Modifier and Type | Method and Description |
---|---|
static ImageResult |
ClassificationVisualizer.getFancyScatterplot(AbstractScoreBasedClassifier cl1,
AbstractScoreBasedClassifier cl2,
REnvironment e,
DataSet... data)
Scatters the classification scores of two binary classifiers for given data.
|
static ImageResult |
ClassificationVisualizer.getScatterplot(AbstractScoreBasedClassifier cl1,
AbstractScoreBasedClassifier cl2,
DataSet class0,
DataSet class1,
REnvironment e,
boolean drawThreshold)
This method returns an
ImageResult containing a scatter plot of
the scores for the given classifiers cl1 and
cl2 . |
static ImageResult |
ClassificationVisualizer.plotScores(AbstractScoreBasedClassifier cl,
DataSet class0,
DataSet class1,
REnvironment e,
int bins,
double density,
String plotOptions)
This method returns an
ImageResult containing a plot of the
histograms of the scores. |
static void |
ClassificationVisualizer.plotScores(AbstractScoreBasedClassifier cl,
DataSet class0,
DataSet class1,
REnvironment e,
int bins,
double density,
String plotOptions,
String fName)
This method creates a pdf containing a plot of the histograms of the
scores.
|
Modifier and Type | Class and Description |
---|---|
class |
SharedStructureClassifier
This class enables you to learn the structure on all classes of the
classifier together.
|