de.jstacs.classifiers.assessment
Class Sampled_RepeatedHoldOutAssessParameterSet

java.lang.Object
  de.jstacs.parameters.ParameterSet
      de.jstacs.classifiers.assessment.ClassifierAssessmentAssessParameterSet
          de.jstacs.classifiers.assessment.Sampled_RepeatedHoldOutAssessParameterSet

All Implemented Interfaces:

GalaxyConvertible, Storable, Cloneable

public class Sampled_RepeatedHoldOutAssessParameterSet
extends ClassifierAssessmentAssessParameterSet

This class implements a ClassifierAssessmentAssessParameterSet that must be used to call the method assess( ... ) of a Sampled_RepeatedHoldOutExperiment. It contains user specific parameters necessary for a run of a Sampled_RepeatedHoldOutExperiment .

Author:

Jens Keilwagen

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

Constructor Summary

Sampled_RepeatedHoldOutAssessParameterSet()
Constructs a new Sampled_RepeatedHoldOutAssessParameterSet with empty parameter values.

Sampled_RepeatedHoldOutAssessParameterSet(DataSet.PartitionMethod dataSplitMethod, int elementLength, boolean exceptionIfMPNotComputable, int repeats, int referenceClass, double percentage, boolean sameLength)
Constructs a new Sampled_RepeatedHoldOutAssessParameterSet with given parameter values.

Sampled_RepeatedHoldOutAssessParameterSet(StringBuffer representation)
The standard constructor for the interface Storable.

Method Summary

Collection<Result>	getAnnotation() Returns a Collection of parameters containing informations about this ClassifierAssessmentAssessParameterSet.
DataSet.PartitionMethod	getDataSplitMethod() Returns the DataSet.PartitionMethod defining how the mutually exclusive random-splits of user supplied data are generated.
double	getPercent() Returns the percentage of user supplied data that is used in each iteration as test data set.
int	getReferenceClass() Returns the index of the reference class.
int	getRepeats() Returns the repeats defined by this Sampled_RepeatedHoldOutAssessParameterSet (repeats defines how many iterations (train and test classifiers) of that Sampled_RepeatedHoldOutExperiment this Sampled_RepeatedHoldOutAssessParameterSet is used with are performed).
boolean	sameLength() Returns true if for test and train data set the sequences of the non-reference classes have the same length as the corresponding sequence of the reference class.

Methods inherited from class de.jstacs.classifiers.assessment.ClassifierAssessmentAssessParameterSet

getElementLength, getExceptionIfMPNotComputable, getStoreAll, setStoreAll

Methods inherited from class de.jstacs.parameters.ParameterSet

clone, fromGalaxy, fromXML, getAllParameterNames, getComment, getComment, getErrorMessage, getIndex, getName, getName, getNumberOfParameters, getParameterAt, getParameterForName, getParent, hasDefaultOrIsSet, initParameterList, initParameterList, isAtomic, isComparable, parametersLoaded, reset, setParent, toGalaxy, toXML

Methods inherited from class java.lang.Object

equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

Constructor Detail

Sampled_RepeatedHoldOutAssessParameterSet

public Sampled_RepeatedHoldOutAssessParameterSet()
                                          throws UnsupportedOperationException,
                                                 ParameterException

Constructs a new Sampled_RepeatedHoldOutAssessParameterSet with empty parameter values. This constructor should only be used to create "filled" Sampled_RepeatedHoldOutAssessParameterSets, i.e. to create Sampled_RepeatedHoldOutAssessParameterSets from a set of values and not to fill it from the platform user-interface.

Throws:

UnsupportedOperationException - if the Sampled_RepeatedHoldOutAssessParameterSet could not be constructed or the parameters could not be loaded

ParameterException - if the parameter for the percentages could not be created

See Also:

ClassifierAssessmentAssessParameterSet.ClassifierAssessmentAssessParameterSet()

Sampled_RepeatedHoldOutAssessParameterSet

public Sampled_RepeatedHoldOutAssessParameterSet(StringBuffer representation)
                                          throws NonParsableException

The standard constructor for the interface Storable. Constructs a Sampled_RepeatedHoldOutAssessParameterSet out of its XML representation.

Parameters:

representation - the XML representation as StringBuffer

Throws:

NonParsableException - if the Sampled_RepeatedHoldOutAssessParameterSet could not be reconstructed out of the XML representation (the StringBuffer representation could not be parsed)

See Also:

ClassifierAssessmentAssessParameterSet.ClassifierAssessmentAssessParameterSet(StringBuffer)

Sampled_RepeatedHoldOutAssessParameterSet

public Sampled_RepeatedHoldOutAssessParameterSet(DataSet.PartitionMethod dataSplitMethod,
                                                 int elementLength,
                                                 boolean exceptionIfMPNotComputable,
                                                 int repeats,
                                                 int referenceClass,
                                                 double percentage,
                                                 boolean sameLength)
                                          throws ParameterException

Constructs a new Sampled_RepeatedHoldOutAssessParameterSet with given parameter values.

Parameters:

dataSplitMethod - defines the method used to split user supplied data into k mutually exclusive random-splits (available options are: DataSet.PartitionMethod.PARTITION_BY_NUMBER_OF_ELEMENTS and DataSet.PartitionMethod.PARTITION_BY_NUMBER_OF_SYMBOLS)

elementLength - defines the length of elements (sequences) the classifiers to be assessed are able to classify

exceptionIfMPNotComputable - a Sampled_RepeatedHoldOutAssessParameterSet is used in combination with an AbstractPerformanceMeasure-object to call assess( ... )-methods of Sampled_RepeatedHoldOutExperiments. If exceptionIfMPNotComputable==true an Exception is thrown in case of a user selected measure parameters that could not be computed.

repeats - the number of repeats 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_RepeatedHoldOutAssessParameterSet is used with

referenceClass - the index of the class for which the complete data set is used, typically this should be the smallest data set (to meet all constraints)

percentage - the percentage of the referenceClass data that should be used as test data in each iteration

sameLength - if true for test and train data set the sequences of the non-reference classes have the same length as the corresponding sequence of the reference class

Throws:

ParameterException - if the parameter for the percentages could not be created

See Also:

DataSet.PartitionMethod

Method Detail

getRepeats

public int getRepeats()

Returns the repeats defined by this Sampled_RepeatedHoldOutAssessParameterSet (repeats defines how many iterations (train and test classifiers) of that Sampled_RepeatedHoldOutExperiment this Sampled_RepeatedHoldOutAssessParameterSet is used with are performed).

Returns:

the repeats defined by this Sampled_RepeatedHoldOutAssessParameterSet (repeats defines how many iterations (train and test classifiers) of that Sampled_RepeatedHoldOutExperiment this Sampled_RepeatedHoldOutAssessParameterSet is used with are performed)

getReferenceClass

public int getReferenceClass()

Returns the index of the reference class.

Returns:

the index of the reference class

getPercent

public double getPercent()

Returns the percentage of user supplied data that is used in each iteration as test data set.

Returns:

the percentage of user supplied data that is used in each iteration as test data set

getDataSplitMethod

public DataSet.PartitionMethod getDataSplitMethod()

Returns the DataSet.PartitionMethod defining how the mutually exclusive random-splits of user supplied data are generated.

Returns:

the DataSet.PartitionMethod defining how the mutually exclusive random-splits of user supplied data are generated

See Also:

DataSet.PartitionMethod

sameLength

public boolean sameLength()

Returns true if for test and train data set the sequences of the non-reference classes have the same length as the corresponding sequence of the reference class.

Returns:

returns true if for test and train data set the sequences of the non-reference classes have the same length as the corresponding sequence of the reference class

getAnnotation

public Collection<Result> getAnnotation()

Description copied from class: ClassifierAssessmentAssessParameterSet

Returns a Collection of parameters containing informations about this ClassifierAssessmentAssessParameterSet.

Overrides:

getAnnotation in class ClassifierAssessmentAssessParameterSet

Returns:

a Collection of parameters containing informations about this ClassifierAssessmentAssessParameterSet