public class RepeatedHoldOutAssessParameterSet extends ClassifierAssessmentAssessParameterSet
ClassifierAssessmentAssessParameterSet
that
must be used to call method assess( ... )
of a
RepeatedHoldOutExperiment
. It contains user specific parameters
necessary for a run of a RepeatedHoldOutExperiment
.ParameterSet.ParameterList
errorMessage, parameters, parent
Constructor and Description |
---|
RepeatedHoldOutAssessParameterSet()
Constructs a new
RepeatedHoldOutAssessParameterSet with empty
parameter values. |
RepeatedHoldOutAssessParameterSet(DataSet.PartitionMethod dataSplitMethod,
int elementLength,
boolean exceptionIfMPNotComputable,
int repeats,
double[] percents)
Constructs a new
RepeatedHoldOutAssessParameterSet with given
parameter values. |
RepeatedHoldOutAssessParameterSet(StringBuffer representation)
The standard constructor for the interface
Storable . |
Modifier and Type | Method and Description |
---|---|
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. |
protected SimpleParameterSet |
getParameterSetContainingASingleDoubleValue(double percent)
|
double[] |
getPercents()
Returns an array containing for each class the percentage of user
supplied data that is used in each iteration as test dataset.
|
int |
getRepeats()
Returns the repeats defined by this
RepeatedHoldOutAssessParameterSet (repeats define how many
iterations (train and test classifiers) of that
RepeatedHoldOutExperiment this
RepeatedHoldOutAssessParameterSet is used with are performed). |
getElementLength, getExceptionIfMPNotComputable, getStoreAll, setStoreAll
clone, fromGalaxy, fromXML, getAllParameterNames, getComment, getComment, getErrorMessage, getIndex, getName, getName, getNumberOfParameters, getParameterAt, getParameterForName, getParent, hasDefaultOrIsSet, initParameterList, initParameterList, isAtomic, isComparable, parametersLoaded, reset, setParent, toGalaxy, toXML
public RepeatedHoldOutAssessParameterSet() throws ParameterException, CloneNotSupportedException
RepeatedHoldOutAssessParameterSet
with empty
parameter values. This constructor should only be used to create
"filled" RepeatedHoldOutAssessParameterSet
s, i.e. to
create RepeatedHoldOutAssessParameterSet
s from a set of values
and not to fill it from the platform user interface.ParameterException
- if the parameters could not be createdCloneNotSupportedException
- if the parameter for the percentages could not be createdClassifierAssessmentAssessParameterSet.ClassifierAssessmentAssessParameterSet()
public RepeatedHoldOutAssessParameterSet(StringBuffer representation) throws NonParsableException
Storable
.
Constructs a RepeatedHoldOutAssessParameterSet
out of its XML
representation.representation
- the XML representation as StringBuffer
NonParsableException
- if the RepeatedHoldOutAssessParameterSet
could not be
reconstructed out of the XML representation (the
StringBuffer
representation
could not be
parsed)ClassifierAssessmentAssessParameterSet.ClassifierAssessmentAssessParameterSet(StringBuffer)
,
Storable
public RepeatedHoldOutAssessParameterSet(DataSet.PartitionMethod dataSplitMethod, int elementLength, boolean exceptionIfMPNotComputable, int repeats, double[] percents) throws ParameterException, CloneNotSupportedException
RepeatedHoldOutAssessParameterSet
with given
parameter values.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 classifyexceptionIfMPNotComputable
- a RepeatedHoldOutAssessParameterSet
is used in
combination with an
AbstractPerformanceMeasure
-object to call
assess( ... )
-methods of
RepeatedHoldOutExperiment
s. 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 datasets, train
classifiers using train datasets and test them using test
datasets) of that RepeatedHoldOutExperiment
this
RepeatedHoldOutAssessParameterSet
is used withpercents
- this array contains class-wise the percentage of the user
supplied data that should be used as test data in each
iteration of that RepeatedHoldOutExperiment
this
RepeatedHoldOutAssessParameterSet
is used withParameterException
- if the parameters could not be createdCloneNotSupportedException
- if the parameter for the percentages could not be createdClassifierAssessmentAssessParameterSet.ClassifierAssessmentAssessParameterSet(int,
boolean)
,
DataSet.PartitionMethod
protected SimpleParameterSet getParameterSetContainingASingleDoubleValue(double percent) throws SimpleParameter.IllegalValueException
ParameterSet
containing a single
double
-SimpleParameter
. This
ParameterSet
is used as a part of the
ExpandableParameterSet
that contains the test data percent for a
specific class. percent
- the double
-value to be contained in the returned
ParameterSet
. If percent==Double.NaN
no
values are contained in the returned ParameterSet
.
(The SimpleParameter
contained in the returned
ParameterSet
contains no value).SimpleParameter
SimpleParameter.IllegalValueException
- if something went wrongpublic int getRepeats()
RepeatedHoldOutAssessParameterSet
(repeats define how many
iterations (train and test classifiers) of that
RepeatedHoldOutExperiment
this
RepeatedHoldOutAssessParameterSet
is used with are performed).RepeatedHoldOutAssessParameterSet
(repeats define how
many iterations (train and test classifiers) of that
RepeatedHoldOutExperiment
this
RepeatedHoldOutAssessParameterSet
is used with are
performed)public double[] getPercents()
public DataSet.PartitionMethod getDataSplitMethod()
DataSet.PartitionMethod
defining how the mutually exclusive
random-splits of user supplied data are generated.DataSet.PartitionMethod
defining how the mutually exclusive
random-splits of user supplied data are generatedDataSet.PartitionMethod
public Collection<Result> getAnnotation()
ClassifierAssessmentAssessParameterSet
Collection
of parameters containing informations about
this ClassifierAssessmentAssessParameterSet
.getAnnotation
in class ClassifierAssessmentAssessParameterSet
Collection
of parameters containing informations about
this ClassifierAssessmentAssessParameterSet