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java.lang.Objectde.jstacs.parameters.ParameterSet
de.jstacs.classifier.assessment.ClassifierAssessmentAssessParameterSet
de.jstacs.classifier.assessment.KFoldCVAssessParameterSet
public class KFoldCVAssessParameterSet
This class implements a ClassifierAssessmentAssessParameterSet that
must be used to call method assess( ... ) of a
KFoldCrossValidation.
It contains user specific parameters necessary for a run of a
KFoldCrossValidation.
| Nested Class Summary |
|---|
| Nested classes/interfaces inherited from class de.jstacs.parameters.ParameterSet |
|---|
ParameterSet.ParameterList |
| Field Summary |
|---|
| Fields inherited from class de.jstacs.parameters.ParameterSet |
|---|
errorMessage, parameters, parent, ranged |
| Constructor Summary | |
|---|---|
KFoldCVAssessParameterSet()
Constructs a new KFoldCVAssessParameterSet with empty parameter
values. |
|
KFoldCVAssessParameterSet(Sample.PartitionMethod dataSplitMethod,
int elementLength,
boolean exceptionIfMPNotComputable,
int k)
Constructs a new KFoldCVAssessParameterSet with given parameter
values. |
|
KFoldCVAssessParameterSet(StringBuffer representation)
The standard constructor for the interface Storable. |
|
| Method Summary | |
|---|---|
ArrayList<Result> |
getAnnotation()
Returns a Collection of parameters containing informations about
this ClassifierAssessmentAssessParameterSet. |
Sample.PartitionMethod |
getDataSplitMethod()
Returns the Sample.PartitionMethod defining how the mutually exclusive
random-splits of user supplied data are generated. |
int |
getK()
Returns the number of mutually exclusive random-splits of user supplied data defined by this KFoldCVAssessParameterSet. |
protected void |
initializeMyParametersArrayList()
Initializes the list of Parameters in this
ClassifierAssessmentAssessParameterSet. |
protected void |
loadParameters()
Loads the parameters for this ParameterSet. |
| Methods inherited from class de.jstacs.classifier.assessment.ClassifierAssessmentAssessParameterSet |
|---|
getElementLength, getExceptionIfMPNotComputable |
| Methods inherited from class de.jstacs.parameters.ParameterSet |
|---|
clone, fromGalaxy, fromXML, getErrorMessage, getId, getIndex, getNumberOfParameters, getNumberOfValues, getParameterAt, getParent, hasDefaultOrIsSet, initParameterList, initParameterList, isAtomic, isRanged, makeRanged, next, parametersLoaded, propagateId, recieveId, replaceParametersWithRangedInstance, reset, resetToFirst, setParent, simplify, toGalaxy, toXML, valuesToString |
| Methods inherited from class java.lang.Object |
|---|
equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait |
| Constructor Detail |
|---|
public KFoldCVAssessParameterSet()
throws UnsupportedOperationException
KFoldCVAssessParameterSet with empty parameter
values. This constructor should only be used to create "filled"
KFoldCVAssessParameterSets, i.e. to create
KFoldCVAssessParameterSets from a set of values and not to fill
it from the platform user interface.
UnsupportedOperationException - if the KFoldCVAssessParameterSet could not be
constructed or the parameters could not be loadedClassifierAssessmentAssessParameterSet.ClassifierAssessmentAssessParameterSet()
public KFoldCVAssessParameterSet(StringBuffer representation)
throws NonParsableException
Storable.
Constructs a KFoldCVAssessParameterSet out of its XML
representation.
representation - the XML representation as StringBuffer
NonParsableException - if the KFoldCVAssessParameterSet could not be
reconstructed out of the XML representation (the
StringBuffer representation could not be
parsed)ClassifierAssessmentAssessParameterSet.ClassifierAssessmentAssessParameterSet(StringBuffer),
Storable
public KFoldCVAssessParameterSet(Sample.PartitionMethod dataSplitMethod,
int elementLength,
boolean exceptionIfMPNotComputable,
int k)
throws SimpleParameter.IllegalValueException
KFoldCVAssessParameterSet with given parameter
values.
dataSplitMethod - defines the method used to split user supplied data into
k mutually exclusive random-splits (available
options are:
Sample.PartitionMethod.PARTITION_BY_NUMBER_OF_ELEMENTS and
Sample.PartitionMethod.PARTITION_BY_NUMBER_OF_SYMBOLS)elementLength - defines the length of elements (sequences) the classifiers to
be assessed are able to classifyexceptionIfMPNotComputable - a KFoldCVAssessParameterSet is used in combination
with a MeasureParameters-object
to call assess( ... )-methods of
KFoldCrossValidations, if
exceptionIfMPNotComputable==true an
Exception is thrown in case of a user selected measure
parameters that could not be computed.k - defines the number of mutually exclusive random-splits of user
supplied data. Each part is used once as a test dataset and
the union of the remaining k-1 parts is once used as train
dataset. Thus k also defines how many (
k) repeated classifier trainings and classifier
evaluations (tests) are performed.
SimpleParameter.IllegalValueException - in case of out-of-range or invalid given parametersClassifierAssessmentAssessParameterSet.ClassifierAssessmentAssessParameterSet(int,
boolean),
Sample.PartitionMethod| Method Detail |
|---|
protected void initializeMyParametersArrayList()
ClassifierAssessmentAssessParameterSetParameters in this
ClassifierAssessmentAssessParameterSet.
initializeMyParametersArrayList in class ClassifierAssessmentAssessParameterSetParameterSet.initParameterList(int initCapacity)
protected void loadParameters()
throws Exception
ParameterSetParameterSet. This is in most cases
done by calling ParameterSet.initParameterList() or
ParameterSet.initParameterList(int) to initialize
ParameterSet.parameters and afterwards filling
ParameterSet.parameters with instances of subclasses of
Parameter.
loadParameters in class ClassifierAssessmentAssessParameterSetException - if the parameters could not be loadedParameter,
ParameterSet.parameters,
ParameterSet.initParameterList(),
ParameterSet.initParameterList(int)public int getK()
KFoldCVAssessParameterSet.
KFoldCVAssessParameterSetpublic Sample.PartitionMethod getDataSplitMethod()
Sample.PartitionMethod defining how the mutually exclusive
random-splits of user supplied data are generated.
Sample.PartitionMethod defining how the mutually exclusive
random-splits of user supplied data are generatedSample.PartitionMethodpublic ArrayList<Result> getAnnotation()
ClassifierAssessmentAssessParameterSetCollection of parameters containing informations about
this ClassifierAssessmentAssessParameterSet.
getAnnotation in class ClassifierAssessmentAssessParameterSetCollection of parameters containing informations about
this ClassifierAssessmentAssessParameterSet
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