Package | Description |
---|---|
de.jstacs.classifiers |
This package provides the framework for any classifier.
|
de.jstacs.classifiers.performanceMeasures |
This package provides the implementations of performance measures that can be used to assess any classifier.
|
de.jstacs.classifiers.trainSMBased |
Provides the classes for
Classifier s that are based on TrainableStatisticalModel s. |
de.jstacs.data.sequences.annotation |
Provides the facilities to annotate
Sequence s using a number of pre-defined annotation types, or additional
implementations of the SequenceAnnotation class. |
de.jstacs.results |
This package provides classes for results and sets of results.
|
de.jstacs.sequenceScores |
Provides all
SequenceScore s, which can be used to score a Sequence , typically using some model assumptions. |
de.jstacs.sequenceScores.differentiable | |
de.jstacs.sequenceScores.statisticalModels.trainable |
Provides all
TrainableStatisticalModel s, which can
be learned from a single DataSet . |
de.jstacs.sequenceScores.statisticalModels.trainable.hmm.models |
The package provides different implementations of hidden Markov models based on
AbstractHMM . |
de.jstacs.sequenceScores.statisticalModels.trainable.mixture |
This package is the super package for any mixture model.
|
de.jstacs.tools | |
de.jstacs.tools.ui.galaxy |
Modifier and Type | Method and Description |
---|---|
ResultSet |
AbstractClassifier.evaluate(AbstractPerformanceMeasureParameterSet<? extends PerformanceMeasure> params,
boolean exceptionIfNotComputeable,
DataSet... s)
This method evaluates the classifier and computes, for instance, the sensitivity for a given specificity, the
area under the ROC curve and so on.
|
ResultSet |
AbstractClassifier.evaluate(AbstractPerformanceMeasureParameterSet<? extends PerformanceMeasure> params,
boolean exceptionIfNotComputeable,
DataSet[] s,
double[][] weights)
This method evaluates the classifier and computes, for instance, the sensitivity for a given specificity, the
area under the ROC curve and so on.
|
ResultSet |
AbstractClassifier.getCharacteristics()
Returns some information characterizing or describing the current
instance of the classifier.
|
Modifier and Type | Method and Description |
---|---|
ResultSet |
PerformanceMeasure.compute(double[][][] classSpecificScores)
This method allows to compute the performance measure of given class specific scores.
|
ResultSet |
AbstractPerformanceMeasure.compute(double[][][] classSpecificScores) |
ResultSet |
PerformanceMeasure.compute(double[][][] classSpecificScores,
double[][] weights)
This method allows to compute the performance measure of given class specific scores.
|
ResultSet |
ConfusionMatrix.compute(double[][][] classSpecificScores,
double[][] weights) |
ResultSet |
AbstractTwoClassPerformanceMeasure.compute(double[][][] classSpecificScores,
double[][] weights) |
ResultSet |
PerformanceMeasure.compute(double[] sortedScoresClass0,
double[] sortedScoresClass1)
This method allows to compute the performance measure of given sorted score ratios.
|
ResultSet |
AbstractPerformanceMeasure.compute(double[] sortedScoresClass0,
double[] sortedScoresClass1) |
ResultSet |
ROCCurve.compute(double[] sortedScoresClass0,
double[] weightsClass0,
double[] sortedScoresClass1,
double[] weightsClass1) |
ResultSet |
PRCurve.compute(double[] sortedScoresClass0,
double[] weightClass0,
double[] sortedScoresClass1,
double[] weightClass1) |
ResultSet |
PerformanceMeasure.compute(double[] sortedScoresClass0,
double[] weightsClass0,
double[] sortedScoresClass1,
double[] weightsClass1)
This method allows to compute the performance measure of given sorted score ratios.
|
ResultSet |
ConfusionMatrix.compute(double[] sortedScoresClass0,
double[] weightClass0,
double[] sortedScoresClass1,
double[] weightClass1) |
Modifier and Type | Method and Description |
---|---|
ResultSet |
TrainSMBasedClassifier.getCharacteristics() |
Modifier and Type | Class and Description |
---|---|
class |
CisRegulatoryModuleAnnotation
Annotation for a cis-regulatory module as defined by a set of
MotifAnnotation s of the motifs in the module. |
class |
IntronAnnotation
Annotation class for an intron as defined by a donor and an acceptor splice
site.
|
class |
LocatedSequenceAnnotation
Class for a
SequenceAnnotation that has a position on the sequence,
e.g for transcription start sites or intron-exon junctions. |
class |
LocatedSequenceAnnotationWithLength
Class for a
SequenceAnnotation that has a position on the sequence
and a length, e.g. |
class |
MotifAnnotation
Class for a
StrandedLocatedSequenceAnnotationWithLength that is a
motif. |
class |
ReferenceSequenceAnnotation
This class implements a
SequenceAnnotation that contains a reference
sequence. |
class |
SequenceAnnotation
Class for a general annotation of a
Sequence . |
class |
SinglePositionSequenceAnnotation
Class for some annotations that consist mainly of one position on a sequence.
|
class |
StrandedLocatedSequenceAnnotationWithLength
Class for a
SequenceAnnotation that has a position, a length and an
orientation on the strand of a Sequence . |
Modifier and Type | Class and Description |
---|---|
class |
MeanResultSet
Class that computes the mean and the standard error of a series of
NumericalResultSet s. |
class |
NumericalResultSet
Class for a set of numerical result values, which are all of the type
NumericalResult . |
Modifier and Type | Field and Description |
---|---|
protected ResultSet[] |
ListResult.list
The internal list of
ResultSet s that are part of this
ListResult |
Modifier and Type | Method and Description |
---|---|
ResultSet |
ListResult.getAnnotation()
Returns a reference to the annotation of this
ListResult . |
ResultSet |
MeanResultSet.getInfos()
Returns some information for this
MeanResultSet . |
ResultSet[] |
ListResult.getRawResult()
Returns a copy of the internal list of
ResultSet s. |
ResultSet[] |
ListResult.getValue() |
Constructor and Description |
---|
ListResult(String name,
String comment,
ResultSet annotation,
Collection<ResultSet> coll)
Creates a new
ListResult from a Collection of ResultSet s and
a ResultSet of annotations, which may provide additional
information on this ListResult . |
ListResult(String name,
String comment,
ResultSet annotation,
ResultSet... results)
Creates a new
ListResult from an array of ResultSet s and
a ResultSet of annotations, which may provide additional
information on this ListResult . |
ListResult(String name,
String comment,
ResultSet annotation,
ResultSet... results)
Creates a new
ListResult from an array of ResultSet s and
a ResultSet of annotations, which may provide additional
information on this ListResult . |
ResultSetResult(String name,
String comment,
ResultSet annotation,
ResultSet result)
Creates a new
ResultSetResult with given name, comment, annotation, and content. |
Constructor and Description |
---|
ListResult(String name,
String comment,
ResultSet annotation,
Collection<ResultSet> coll)
Creates a new
ListResult from a Collection of ResultSet s and
a ResultSet of annotations, which may provide additional
information on this ListResult . |
Modifier and Type | Method and Description |
---|---|
ResultSet |
SequenceScore.getCharacteristics()
Returns some information characterizing or describing the current
instance.
|
Modifier and Type | Method and Description |
---|---|
ResultSet |
AbstractDifferentiableSequenceScore.getCharacteristics() |
Modifier and Type | Method and Description |
---|---|
ResultSet |
CompositeTrainSM.getCharacteristics() |
ResultSet |
AbstractTrainableStatisticalModel.getCharacteristics() |
Modifier and Type | Method and Description |
---|---|
ResultSet |
HigherOrderHMM.getCharacteristics() |
Modifier and Type | Method and Description |
---|---|
ResultSet |
AbstractMixtureTrainSM.getCharacteristics() |
Constructor and Description |
---|
ToolResult(String name,
String comment,
ResultSet annotation,
ResultSet result,
ParameterSet toolParameters,
String toolName,
Date finished)
Creates a new
ToolResult with most arguments identical to those of a ListResult . |
Modifier and Type | Method and Description |
---|---|
void |
GalaxyAdaptor.addResultSet(ResultSet res,
boolean exportAll,
boolean includeInSummary)
Adds a set of results to the results of a program run.
|