weka.classifiers.trees.j48Consolidated
public class InstancesConsolidated extends weka.core.Instances
Modifier and Type | Field and Description |
---|---|
private static long |
serialVersionUID
for serialization
|
Constructor and Description |
---|
InstancesConsolidated(weka.core.Instances dataset)
Constructor calling the constructor of the superclass
(Not necessary if the above methods are moved to the official class 'Instances')
|
InstancesConsolidated(weka.core.Instances source,
int first,
int toCopy)
Constructor calling the constructor of the superclass
(Not necessary if the above methods are moved to the official class 'Instances')
|
Modifier and Type | Method and Description |
---|---|
void |
add(InstancesConsolidated instances)
Adds a set of instances to the end of the set.
|
InstancesConsolidated[] |
getClasses()
Gets the vector of classes of the dataset like a set of samples
|
int[] |
getClassesSize(InstancesConsolidated[] classesVector)
Gets the vector with the size of each class of the dataset
|
private int[] |
getClassIndices()
Creates an index containing the position where each class starts in
the dataset.
|
void |
printClassesInformation(int dataSize,
int iMinClass,
int[] classSizeVector)
Prints information about the size of the classes and their proportions
and indicates which is the minority class of the sample
|
add, add, attribute, attribute, attributeStats, attributeToDoubleArray, checkForAttributeType, checkForStringAttributes, checkInstance, classAttribute, classIndex, compactify, copyInstances, delete, delete, deleteAttributeAt, deleteAttributeType, deleteStringAttributes, deleteWithMissing, deleteWithMissing, deleteWithMissingClass, enumerateAttributes, enumerateInstances, equalHeaders, equalHeadersMsg, firstInstance, freshAttributeInfo, get, getRandomNumberGenerator, getRevision, initialize, insertAttributeAt, instance, instancesAndWeights, kthSmallestValue, kthSmallestValue, lastInstance, main, meanOrMode, meanOrMode, mergeInstances, numAttributes, numClasses, numDistinctValues, numDistinctValues, numInstances, randomize, readInstance, relationName, remove, renameAttribute, renameAttribute, renameAttributeValue, renameAttributeValue, resample, resampleWithWeights, resampleWithWeights, resampleWithWeights, resampleWithWeights, resampleWithWeights, resampleWithWeights, resampleWithWeights, set, setClass, setClassIndex, setRelationName, size, sort, sort, stratify, stratStep, stringFreeStructure, stringWithoutHeader, sumOfWeights, swap, test, testCV, toString, toSummaryString, trainCV, trainCV, variance, variance
addAll, clear, equals, hashCode, indexOf, iterator, lastIndexOf, listIterator, listIterator, removeRange, subList
addAll, contains, containsAll, isEmpty, remove, removeAll, retainAll, toArray, toArray
private static final long serialVersionUID
public InstancesConsolidated(weka.core.Instances dataset)
dataset
- the set to be copiedpublic InstancesConsolidated(weka.core.Instances source, int first, int toCopy)
source
- the set of instances from which a subset
is to be createdfirst
- the index of the first instance to be copiedtoCopy
- the number of instances to be copiedpublic InstancesConsolidated[] getClasses()
private int[] getClassIndices()
public int[] getClassesSize(InstancesConsolidated[] classesVector)
classesVector
- the vector of classes of the dataset like a set of samplespublic void add(InstancesConsolidated instances)
instances
- the set of instances to be addedpublic void printClassesInformation(int dataSize, int iMinClass, int[] classSizeVector)
dataSize
- the size of original sampleiMinClass
- the index of the minority class in the original sampleclassSizeVector
- the vector with the size of each class of the dataset