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java.lang.Objectde.jstacs.parameters.ParameterSet
de.jstacs.classifier.assessment.ClassifierAssessmentAssessParameterSet
de.jstacs.classifier.assessment.Sampled_RepeatedHoldOutAssessParameterSet
public class Sampled_RepeatedHoldOutAssessParameterSet
| 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 |
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alternativeInstanceClass, errorMessage, parameters, parent, ranged |
| Constructor Summary | |
|---|---|
|
Sampled_RepeatedHoldOutAssessParameterSet()
inherited from ClassifierAssessmentAssessParameterSet |
protected |
Sampled_RepeatedHoldOutAssessParameterSet(Class alternativeInstanceClass)
inherited from ClassifierAssessmentAssessParameterSet |
|
Sampled_RepeatedHoldOutAssessParameterSet(Sample.PartitionMethod dataSplitMethod,
int elementLength,
boolean exceptionIfMPNotComputable,
int repeats,
int referenceClass,
double percentage,
boolean sameLength)
|
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Sampled_RepeatedHoldOutAssessParameterSet(StringBuffer representation)
inherited from ClassifierAssessmentAssessParameterSet |
| Method Summary | |
|---|---|
Collection<Result> |
getAnnotation()
|
Sample.PartitionMethod |
getDataSplitMethod()
|
String |
getInstanceComment()
Returns a comment (a textual description) of the class that can be constructed using this ParameterSet. |
String |
getInstanceName()
Returns the name of an instance of the class that can be constructed using this ParameterSet. |
double |
getPercent()
|
int |
getReferenceClass()
|
int |
getRepeats()
|
protected void |
initializeMyParametersArrayList()
Initializes the list of Parameters in this ParameterSet. |
protected void |
loadParameters()
Loads the parameters for this ParameterSet. |
boolean |
sameLength()
|
| Methods inherited from class de.jstacs.classifier.assessment.ClassifierAssessmentAssessParameterSet |
|---|
getAllClassifierAssessmentAssessParameterSets, getElementLength, getExceptionIfMPNotComputable |
| Methods inherited from class de.jstacs.parameters.ParameterSet |
|---|
clone, fromXML, getErrorMessage, getId, getInstance, getInstanceClass, getNumberOfParameters, getNumberOfValues, getParameterAt, getParent, hasDefaultOrIsSet, initParameterList, initParameterList, isAtomic, isRanged, makeRanged, next, parametersLoaded, propagateId, recieveId, replaceParametersWithRangedInstance, reset, resetToFirst, setAlternativeInstanceClass, setParent, simplify, toXML, valuesToString |
| Methods inherited from class java.lang.Object |
|---|
equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait |
| Constructor Detail |
|---|
protected Sampled_RepeatedHoldOutAssessParameterSet(Class alternativeInstanceClass)
ClassifierAssessmentAssessParameterSet
public Sampled_RepeatedHoldOutAssessParameterSet()
throws UnsupportedOperationException
ClassifierAssessmentAssessParameterSet
UnsupportedOperationException
public Sampled_RepeatedHoldOutAssessParameterSet(StringBuffer representation)
throws NonParsableException
ClassifierAssessmentAssessParameterSet
NonParsableException
public Sampled_RepeatedHoldOutAssessParameterSet(Sample.PartitionMethod dataSplitMethod,
int elementLength,
boolean exceptionIfMPNotComputable,
int repeats,
int referenceClass,
double percentage,
boolean sameLength)
throws SimpleParameter.IllegalValueException
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) See docu of Sample
for further details.elementLength - defines the length of elements (sequences) the classifiers to be assessed are able to classifyexceptionIfMPNotComputable - a Sampled_RepeatedHoldOutParameterSet is used in combination with an
MeasureParameters-object to call assess-methods of
Sampled_RepeatedHoldOutExperiments. If exceptionIfMPNotComputable=true
then an expection is thrown in case of a selected measure-parameters that could not be computed.repeats - the number of repeates of each iteration (mutually exclusive, randomly split data to obtain test- and
train-data-sets, train classifiers using train-data-sets and test them using test-data-sets) of that
RepeatedHoldOutExperiment this Sampled_RepatedHoldOutAssessParameterSet
is used withreferenceClass - the index of the class for which the complete data set is usedpercentage - the percentage of the referenceClass-data that should be used as test-data in each
iterationsameLength - if true then for test respectively train data set the sequences of the non-reference
classes have the same length as the corresponding sequence of the reference class
SimpleParameter.IllegalValueException - is thrown in case of out-of-range or invalid given parameters| Method Detail |
|---|
protected void initializeMyParametersArrayList()
ClassifierAssessmentAssessParameterSetParameters in this ParameterSet.
initializeMyParametersArrayList in class ClassifierAssessmentAssessParameterSet
protected void loadParameters()
throws Exception
ParameterSetParameterSet. This is in
most cases done by simply creating a new ArrayList<Parameter> for the
field parameters/code>
and filling it with instances of subclasses of Parameter
- Overrides:
loadParameters in class ClassifierAssessmentAssessParameterSet
- Throws:
Exception - an Exception is thrown if the parameters could not be loaded- See Also:
ParameterSet.parameters,
Parameter
public String getInstanceName()
ParameterSetParameterSet.
getInstanceName in class ClassifierAssessmentAssessParameterSetpublic String getInstanceComment()
ParameterSetParameterSet.
getInstanceComment in class ClassifierAssessmentAssessParameterSetpublic int getRepeats()
Sampled_RepatedHoldOutAssessParameterSet (repeats defines how
many iterations (train and test classifiers) of that Sampled_RepeatedHoldOutExperiment
this Sampled_RepeatedHoldOutAssessParameterSet is used with are performed)public int getReferenceClass()
public double getPercent()
public Sample.PartitionMethod getDataSplitMethod()
Sample.PartitionMethod defining how the mutually exclusive, random-splits
of user-supplied data are generated. See class Sample for further details.public boolean sameLength()
true if for test respectively train data set the sequences of the non-reference
classes have the same length as the corresponding sequence of the reference classpublic Collection<Result> getAnnotation()
getAnnotation in class ClassifierAssessmentAssessParameterSetClassifierAssessmentAssessParameterSet
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