Trainset: Trainning set.
In D2MCS: Data Driving Multiple Classifier System
Trainset R Documentation
Trainning set.
Description
The Trainset is used to perform training
operations over M.L. models. A target class should be defined to guarantee a
full compatibility with supervised models.
Details
Use Dataset object to ensure the creation of a valid
Trainset object.
Methods
Public methods
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Method new()
Method for initializing the object arguments during runtime.
Usage
Trainset$new(cluster.dist, class.name, class.values, positive.class)
Arguments
cluster.distThe type of cluster distribution used as basis
to build the Trainset. See
GenericClusteringStrategy for more information.
class.nameUsed to specify the name of the column containing the
target class.
class.valuesSpecifies all the possible values of the target class.
positive.classA character with the value of the
positive class.
Method getPositiveClass()
The function is used to obtain the value of the positive
class.
Usage
Trainset$getPositiveClass()
Returns
A numeric value with the positive class value.
Method getClassName()
The function is used to return the name of the target class.
Usage
Trainset$getClassName()
Returns
A character vector with length 1.
Method getClassValues()
The function is used to compute all the possible target class
values.
Usage
Trainset$getClassValues()
Returns
A factor value.
Method getColumnNames()
The function returns the name of the columns comprising
an specific cluster distribution.
Usage
Trainset$getColumnNames(num.cluster)
Arguments
num.clusterA numeric value used to specify the cluster
number of the cluster distribution used when creating the
Trainset.
Returns
A character vector with all column names.
Method getFeatureValues()
The function returns the values of the columns comprising
an specific cluster distribution. Target class is omitted.
Usage
Trainset$getFeatureValues(num.cluster)
Arguments
num.clusterA numeric value used to specify the cluster
number of the cluster distribution used when creating the
Trainset.
Returns
A data.frame with the values of the features comprising
the selected cluster distribution.
Method getInstances()
The function returns the values of the columns comprising
an specific cluster distribution. Target class is included as the last
column.
Usage
Trainset$getInstances(num.cluster)
Arguments
num.clusterA numeric value used to specify the cluster
number of the cluster distribution used when creating the
Trainset.
Returns
A data.frame with the values of the features comprising
the selected cluster distribution.
Method getNumClusters()
The function obtains the number of groups (clusters) that
forms the cluster distribution.
Usage
Trainset$getNumClusters()
Returns
A numeric vector of size 1.
See Also
Dataset, DatasetLoader,
Subset, GenericClusteringStrategy
D2MCS documentation built on Aug. 23, 2022, 5:07 p.m.
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| Trainset | R Documentation |
Trainning set.
Description
The Trainset is used to perform training
operations over M.L. models. A target class should be defined to guarantee a
full compatibility with supervised models.
Details
Use Dataset object to ensure the creation of a valid
Trainset object.
Methods
Public methods
Method new()
Method for initializing the object arguments during runtime.
Usage
Trainset$new(cluster.dist, class.name, class.values, positive.class)
Arguments
cluster.distThe type of cluster distribution used as basis to build the
Trainset. SeeGenericClusteringStrategyfor more information.class.nameUsed to specify the name of the column containing the target class.
class.valuesSpecifies all the possible values of the target class.
positive.classA character with the value of the positive class.
Method getPositiveClass()
The function is used to obtain the value of the positive class.
Usage
Trainset$getPositiveClass()
Returns
A numeric value with the positive class value.
Method getClassName()
The function is used to return the name of the target class.
Usage
Trainset$getClassName()
Returns
A character vector with length 1.
Method getClassValues()
The function is used to compute all the possible target class values.
Usage
Trainset$getClassValues()
Returns
A factor value.
Method getColumnNames()
The function returns the name of the columns comprising an specific cluster distribution.
Usage
Trainset$getColumnNames(num.cluster)
Arguments
num.clusterA numeric value used to specify the cluster number of the cluster distribution used when creating the
Trainset.
Returns
A character vector with all column names.
Method getFeatureValues()
The function returns the values of the columns comprising an specific cluster distribution. Target class is omitted.
Usage
Trainset$getFeatureValues(num.cluster)
Arguments
num.clusterA numeric value used to specify the cluster number of the cluster distribution used when creating the
Trainset.
Returns
A data.frame with the values of the features comprising the selected cluster distribution.
Method getInstances()
The function returns the values of the columns comprising an specific cluster distribution. Target class is included as the last column.
Usage
Trainset$getInstances(num.cluster)
Arguments
num.clusterA numeric value used to specify the cluster number of the cluster distribution used when creating the
Trainset.
Returns
A data.frame with the values of the features comprising the selected cluster distribution.
Method getNumClusters()
The function obtains the number of groups (clusters) that forms the cluster distribution.
Usage
Trainset$getNumClusters()
Returns
A numeric vector of size 1.
See Also
Dataset, DatasetLoader,
Subset, GenericClusteringStrategy
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