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## de.jstacs.classifier.assessment
Class KFoldCVAssessParameterSet

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

All Implemented Interfaces:
  GalaxyConvertible, RangeIterator, Storable, Cloneable

    public class KFoldCVAssessParameterSet

extends ClassifierAssessmentAssessParameterSet

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`.

Author:
  Andre Gohr (bioinf (nospam:.) ag (nospam:@) googlemail (nospam:.) com)

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 `Parameter`s 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

### KFoldCVAssessParameterSet

    public KFoldCVAssessParameterSet()
                              throws UnsupportedOperationException

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

  Throws:
    `UnsupportedOperationException` - if the `KFoldCVAssessParameterSet` could not be constructed or the parameters could not be loaded
  See Also:
    `ClassifierAssessmentAssessParameterSet.ClassifierAssessmentAssessParameterSet()`

### KFoldCVAssessParameterSet

    public KFoldCVAssessParameterSet(StringBuffer representation)
                              throws NonParsableException

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

  Parameters:
    `representation` - the XML representation as `StringBuffer`
  Throws:
    `NonParsableException` - if the `KFoldCVAssessParameterSet` could not be reconstructed out of the XML representation (the `StringBuffer` `representation` could not be parsed)
  See Also:
    `ClassifierAssessmentAssessParameterSet.ClassifierAssessmentAssessParameterSet(StringBuffer)`, `Storable`

### KFoldCVAssessParameterSet

    public KFoldCVAssessParameterSet(Sample.PartitionMethod dataSplitMethod,
                                     int elementLength,
                                     boolean exceptionIfMPNotComputable,
                                     int k)
                              throws SimpleParameter.IllegalValueException

  Constructs a new `KFoldCVAssessParameterSet` with given parameter values.

  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`)
    `elementLength` - defines the length of elements (sequences) the classifiers to be assessed are able to classify
    `exceptionIfMPNotComputable` - a `KFoldCVAssessParameterSet` is used in combination with a `MeasureParameters`-object to call `assess( ... )`-methods of `KFoldCrossValidation`s, 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.
  Throws:
    `SimpleParameter.IllegalValueException` - in case of out-of-range or invalid given parameters
  See Also:
    `ClassifierAssessmentAssessParameterSet.ClassifierAssessmentAssessParameterSet(int, boolean)`, `Sample.PartitionMethod`

Method Detail

### initializeMyParametersArrayList

    protected void initializeMyParametersArrayList()

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

  Overrides:
    `initializeMyParametersArrayList` in class `ClassifierAssessmentAssessParameterSet`
  See Also:
    `ParameterSet.initParameterList(int initCapacity)`

### loadParameters

    protected void loadParameters()
                           throws Exception

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

  Overrides:
    `loadParameters` in class `ClassifierAssessmentAssessParameterSet`
  Throws:
    `Exception` - if the parameters could not be loaded
  See Also:
    `Parameter`, `ParameterSet.parameters`, `ParameterSet.initParameterList()`, `ParameterSet.initParameterList(int)`

### getK

    public int getK()

  Returns the number of mutually exclusive random-splits of user supplied data defined by this `KFoldCVAssessParameterSet`.

  Returns:
    the number of mutually exclusive random-splits of user-supplied data defined by this `KFoldCVAssessParameterSet`

### getDataSplitMethod

    public Sample.PartitionMethod getDataSplitMethod()

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

  Returns:
    the `Sample.PartitionMethod` defining how the mutually exclusive random-splits of user supplied data are generated
  See Also:
    `Sample.PartitionMethod`

### getAnnotation

    public ArrayList<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`

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