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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 |
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Nested classes/interfaces inherited from class de.jstacs.parameters.ParameterSet |
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ParameterSet.ParameterList |
Field Summary |
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Fields inherited from class de.jstacs.parameters.ParameterSet |
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alternativeInstanceClass, errorMessage, parameters, parent, ranged |
Constructor Summary | |
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Sampled_RepeatedHoldOutAssessParameterSet()
inherited from ClassifierAssessmentAssessParameterSet |
protected |
Sampled_RepeatedHoldOutAssessParameterSet(Class alternativeInstanceClass)
inherited from ClassifierAssessmentAssessParameterSet |
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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 | |
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Collection<Result> |
getAnnotation()
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Sample.PartitionMethod |
getDataSplitMethod()
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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()
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int |
getReferenceClass()
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int |
getRepeats()
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protected void |
initializeMyParametersArrayList()
Initializes the list of Parameter s in this ParameterSet . |
protected void |
loadParameters()
Loads the parameters for this ParameterSet . |
boolean |
sameLength()
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Methods inherited from class de.jstacs.classifier.assessment.ClassifierAssessmentAssessParameterSet |
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getAllClassifierAssessmentAssessParameterSets, getElementLength, getExceptionIfMPNotComputable |
Methods inherited from class de.jstacs.parameters.ParameterSet |
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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 |
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equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait |
Constructor Detail |
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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_RepeatedHoldOutExperiment
s. 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 parametersMethod Detail |
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protected void initializeMyParametersArrayList()
ClassifierAssessmentAssessParameterSet
Parameter
s in this ParameterSet
.
initializeMyParametersArrayList
in class ClassifierAssessmentAssessParameterSet
protected void loadParameters() throws Exception
ParameterSet
ParameterSet
. 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()
ParameterSet
ParameterSet
.
getInstanceName
in class ClassifierAssessmentAssessParameterSet
public String getInstanceComment()
ParameterSet
ParameterSet
.
getInstanceComment
in class ClassifierAssessmentAssessParameterSet
public 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 ClassifierAssessmentAssessParameterSet
ClassifierAssessmentAssessParameterSet
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