public class Sampled_RepeatedHoldOutAssessParameterSet extends ClassifierAssessmentAssessParameterSet
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
.ParameterSet.ParameterList
errorMessage, parameters, parent
Constructor and Description |
---|
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 . |
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. |
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. |
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 Sampled_RepeatedHoldOutAssessParameterSet() throws UnsupportedOperationException, ParameterException
Sampled_RepeatedHoldOutAssessParameterSet
with
empty parameter values. This constructor should only be used to create
"filled" Sampled_RepeatedHoldOutAssessParameterSet
s,
i.e. to create Sampled_RepeatedHoldOutAssessParameterSet
s from a
set of values and not to fill it from the platform user-interface.UnsupportedOperationException
- if the Sampled_RepeatedHoldOutAssessParameterSet
could not be constructed or the parameters could not be
loadedParameterException
- if the parameter for the percentages could not be createdClassifierAssessmentAssessParameterSet.ClassifierAssessmentAssessParameterSet()
public Sampled_RepeatedHoldOutAssessParameterSet(StringBuffer representation) throws NonParsableException
Storable
.
Constructs a Sampled_RepeatedHoldOutAssessParameterSet
out of its
XML representation.representation
- the XML representation as StringBuffer
NonParsableException
- if the Sampled_RepeatedHoldOutAssessParameterSet
could not be reconstructed out of the XML representation (the
StringBuffer
representation
could not be
parsed)ClassifierAssessmentAssessParameterSet.ClassifierAssessmentAssessParameterSet(StringBuffer)
public Sampled_RepeatedHoldOutAssessParameterSet(DataSet.PartitionMethod dataSplitMethod, int elementLength, boolean exceptionIfMPNotComputable, int repeats, int referenceClass, double percentage, boolean sameLength) throws ParameterException
Sampled_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 Sampled_RepeatedHoldOutAssessParameterSet
is used in
combination with an
AbstractPerformanceMeasure
-object to call
assess( ... )
-methods of
Sampled_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 data sets, train
classifiers using train data sets and test them using test
data sets) of that RepeatedHoldOutExperiment
this
Sampled_RepeatedHoldOutAssessParameterSet
is used withreferenceClass
- 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 iterationsameLength
- 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 classParameterException
- if the parameter for the percentages could not be createdDataSet.PartitionMethod
public int getRepeats()
Sampled_RepeatedHoldOutAssessParameterSet
(repeats defines how
many iterations (train and test classifiers) of that
Sampled_RepeatedHoldOutExperiment
this
Sampled_RepeatedHoldOutAssessParameterSet
is used with are
performed).Sampled_RepeatedHoldOutAssessParameterSet
(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 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 boolean sameLength()
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.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 classpublic Collection<Result> getAnnotation()
ClassifierAssessmentAssessParameterSet
Collection
of parameters containing informations about
this ClassifierAssessmentAssessParameterSet
.getAnnotation
in class ClassifierAssessmentAssessParameterSet
Collection
of parameters containing informations about
this ClassifierAssessmentAssessParameterSet