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## de.jstacs.classifier.assessment
Class Sampled_RepeatedHoldOutAssessParameterSet

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

All Implemented Interfaces:
  RangeIterator, Storable, Cloneable

    public class Sampled_RepeatedHoldOutAssessParameterSet

extends ClassifierAssessmentAssessParameterSet

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
`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)`
`` | `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 `Parameter`s 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

### Sampled_RepeatedHoldOutAssessParameterSet

    protected Sampled_RepeatedHoldOutAssessParameterSet(Class alternativeInstanceClass)

  inherited from `ClassifierAssessmentAssessParameterSet`

### Sampled_RepeatedHoldOutAssessParameterSet

    public Sampled_RepeatedHoldOutAssessParameterSet()
                                              throws UnsupportedOperationException

  inherited from `ClassifierAssessmentAssessParameterSet`

  Throws:
    `UnsupportedOperationException`

### Sampled_RepeatedHoldOutAssessParameterSet

    public Sampled_RepeatedHoldOutAssessParameterSet(StringBuffer representation)
                                              throws NonParsableException

  inherited from `ClassifierAssessmentAssessParameterSet`

  Throws:
    `NonParsableException`

### Sampled_RepeatedHoldOutAssessParameterSet

    public Sampled_RepeatedHoldOutAssessParameterSet(Sample.PartitionMethod dataSplitMethod,
                                                     int elementLength,
                                                     boolean exceptionIfMPNotComputable,
                                                     int repeats,
                                                     int referenceClass,
                                                     double percentage,
                                                     boolean sameLength)
                                              throws SimpleParameter.IllegalValueException

Parameters:
  `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 classify
  `exceptionIfMPNotComputable` - 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 with
  `referenceClass` - the index of the class for which the complete data set is used
  `percentage` - the percentage of the `referenceClass`-data that should be used as test-data in each iteration
  `sameLength` - 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
Throws:
  `SimpleParameter.IllegalValueException` - is thrown in case of out-of-range or invalid given parameters

Method Detail

### initializeMyParametersArrayList

    protected void initializeMyParametersArrayList()

  Description copied from class: `ClassifierAssessmentAssessParameterSet`
  Initializes the list of `Parameter`s in this `ParameterSet`.

  Overrides:
    `initializeMyParametersArrayList` in class `ClassifierAssessmentAssessParameterSet`

### loadParameters

    protected void loadParameters()
                           throws Exception

  Description copied from class: `ParameterSet`
  Loads the parameters for this `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`

### getInstanceName

    public String getInstanceName()

  Description copied from class: `ParameterSet`
  Returns the name of an instance of the class that can be constructed using this `ParameterSet`.

  Overrides:
    `getInstanceName` in class `ClassifierAssessmentAssessParameterSet`
  Returns:
    the name

### getInstanceComment

    public String getInstanceComment()

  Description copied from class: `ParameterSet`
  Returns a comment (a textual description) of the class that can be constructed using this `ParameterSet`.

  Overrides:
    `getInstanceComment` in class `ClassifierAssessmentAssessParameterSet`
  Returns:
    the comment

### getRepeats

    public int getRepeats()

  Returns:
    the repeates defined by this `Sampled_RepatedHoldOutAssessParameterSet` (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

### getPercent

    public double getPercent()

  Returns:
    the percentage of user supplied-data that is used in each iterations as test-data-set

### getDataSplitMethod

    public Sample.PartitionMethod getDataSplitMethod()

  Returns:
    The `Sample.PartitionMethod` defining how the mutually exclusive, random-splits of user-supplied data are generated. See class `Sample` for further details.

### sameLength

    public boolean sameLength()

  Returns:
    returns `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 class

### getAnnotation

    public Collection<Result> getAnnotation()

  Overrides:
    `getAnnotation` in class `ClassifierAssessmentAssessParameterSet`
  Returns:
    collection of parameters containing informations about this `ClassifierAssessmentAssessParameterSet`

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