A B C D E G H I L M N O R S T W Z

A

AbsoluteLossFunction - Class in weka.classifiers.misc.monotone
Class implementing the absolute loss function, this means the returned loss is the abolute value of the difference between the predicted and actual value.
AbsoluteLossFunction() - Constructor for class weka.classifiers.misc.monotone.AbsoluteLossFunction
 

B

balancedTipText() - Method in class weka.classifiers.misc.monotone.OSDLCore
Returns a string suitable for displaying in the gui/experimenter.
BitMatrix - Interface in weka.classifiers.misc.monotone
Interface specifying a simple matrix of booleans.
BooleanBitMatrix - Class in weka.classifiers.misc.monotone
This class is a very simple implementation of a BitMatrix.
BooleanBitMatrix(int, int) - Constructor for class weka.classifiers.misc.monotone.BooleanBitMatrix
Construct a BitMatrix with the indicated number of rows and columns.
BooleanBitMatrix(BooleanBitMatrix) - Constructor for class weka.classifiers.misc.monotone.BooleanBitMatrix
A copy constructor.
buildClassifier(Instances) - Method in class weka.classifiers.misc.monotone.OSDLCore
Builds the classifier.

C

classificationTypeTipText() - Method in class weka.classifiers.misc.monotone.OSDLCore
Returns the tip text for this property.
classifyInstance(Instance) - Method in class weka.classifiers.misc.monotone.OSDLCore
Classifies a given instance using the current settings of the classifier.
classifyInstances(Instances, Classifier) - Static method in class weka.classifiers.misc.monotone.InstancesUtil
Classify a set of instances using a given classifier.
clear(int, int) - Method in interface weka.classifiers.misc.monotone.BitMatrix
Clears the bit at the specified position.
clear(int, int) - Method in class weka.classifiers.misc.monotone.BooleanBitMatrix
Clears the bit at the specified position.
columnCount(int) - Method in interface weka.classifiers.misc.monotone.BitMatrix
Counts the number of bits that are set in the specified column.
columnCount(int) - Method in class weka.classifiers.misc.monotone.BooleanBitMatrix
Counts the number of bits that are set in the specified column.
columns() - Method in interface weka.classifiers.misc.monotone.BitMatrix
Gets the number of columns.
columns() - Method in class weka.classifiers.misc.monotone.BooleanBitMatrix
Gets the number of columns.
comparable(Instance, Instance) - Static method in class weka.classifiers.misc.monotone.InstancesUtil
Checks if two instances are comparable in the data space, this is ignoring the class attribute.
compare(Object, Object) - Method in class weka.classifiers.misc.monotone.InstancesComparator
Compares two objects (instances) with respect to the attribute this comparator is constructed on.
containsIgnoreClass(Instances, Instance) - Static method in class weka.classifiers.misc.monotone.InstancesUtil
Get the index of an instance in a set of instances, where instances are compared ignoring the class attribute.
Coordinates - Class in weka.classifiers.misc.monotone
This is a simple implementation of the data space.
Coordinates(Instance) - Constructor for class weka.classifiers.misc.monotone.Coordinates
Create the Coordinates for the given instance.
countValues(Instances, int) - Static method in class weka.classifiers.misc.monotone.InstancesUtil
Return a histogram of the values for the specified attribute.
crossValidate() - Method in class weka.classifiers.misc.monotone.OSDLCore
Tunes the interpolation parameter using the current settings of the classifier.
crossValidate(double, double, int, int) - Method in class weka.classifiers.misc.monotone.OSDLCore
Tune the interpolation parameter using leave-one-out cross validation, the loss function used is the 1-0 loss function.
crossValidate(double, double, int, int, double[], NominalLossFunction) - Method in class weka.classifiers.misc.monotone.OSDLCore
Tune the interpolation parameter using leave-one-out cross validation.
CT_MAXPROB - Static variable in class weka.classifiers.misc.monotone.OSDLCore
Constant indicating that the classification type is the mode of the distribution.
CT_MEDIAN - Static variable in class weka.classifiers.misc.monotone.OSDLCore
Constant indicating that the classification type is the median.
CT_MEDIAN_REAL - Static variable in class weka.classifiers.misc.monotone.OSDLCore
Constant indicating that the classification type is the median, but not rounded to the nearest class.
CT_REGRESSION - Static variable in class weka.classifiers.misc.monotone.OSDLCore
Constant indicating that the classification type is regression (probabilistic weighted sum).
CT_WEIGHTED_SUM - Static variable in class weka.classifiers.misc.monotone.OSDLCore
Constant indicating that the classification type is the probabilistic weighted sum.
CumulativeDiscreteDistribution - Class in weka.classifiers.misc.monotone
Represents a discrete cumulative probability distribution over a totally ordered discrete set.
CumulativeDiscreteDistribution(DiscreteEstimator) - Constructor for class weka.classifiers.misc.monotone.CumulativeDiscreteDistribution
Create a discrete cumulative probability distribution based on a DiscreteEstimator.
CumulativeDiscreteDistribution(DiscreteDistribution) - Constructor for class weka.classifiers.misc.monotone.CumulativeDiscreteDistribution
Create a CumulativeDiscreteDistribution based on a DiscreteDistribution.
CumulativeDiscreteDistribution(double[]) - Constructor for class weka.classifiers.misc.monotone.CumulativeDiscreteDistribution
Create a CumulativeDiscreteDistribution based on an array of doubles.
cumulativeDistributionForInstance(Instance) - Method in class weka.classifiers.misc.monotone.OSDLCore
Calculates the cumulative class probabilities for the given test instance.

D

dimension() - Method in class weka.classifiers.misc.monotone.Coordinates
Gets the dimension of the data space, this is the number of attributes, exluding the class attribute.
DiscreteDistribution - Class in weka.classifiers.misc.monotone
This class represents a discrete probability distribution over a finite number of values.
DiscreteDistribution(DiscreteEstimator) - Constructor for class weka.classifiers.misc.monotone.DiscreteDistribution
Create a DiscreteDistribution based on a DiscreteEstimator.
DiscreteDistribution(CumulativeDiscreteDistribution) - Constructor for class weka.classifiers.misc.monotone.DiscreteDistribution
Create a DiscreteDistribution based on a CumulativeDiscreteDistribution.
DiscreteDistribution(double[]) - Constructor for class weka.classifiers.misc.monotone.DiscreteDistribution
Create a DiscreteDistribution based on an array of doubles.
distributionForInstance(Instance) - Method in class weka.classifiers.misc.monotone.OSDLCore
Calculates the class probabilities for the given test instance.
distributionForInstance(Instance) - Method in class weka.classifiers.misc.OSDL
Use classifyInstance from OSDLCore and assign probability one to the chosen label.
DistributionUtils - Class in weka.classifiers.misc.monotone
Class with some simple methods acting on CumulativeDiscreteDistribution.
DistributionUtils() - Constructor for class weka.classifiers.misc.monotone.DistributionUtils
 
doubt(Instance, Instance) - Static method in class weka.classifiers.misc.monotone.InstancesUtil
Checks it two instances give rise to doubt.

E

EnumerationIterator - Class in weka.classifiers.misc.monotone
Implementation of a simple wrapper class for the Enumeration interface.
EnumerationIterator(Enumeration) - Constructor for class weka.classifiers.misc.monotone.EnumerationIterator
Construct an EnumerationIterator on basis of on Enumeration.
equalIgnoreClass(Instance, Instance) - Static method in class weka.classifiers.misc.monotone.InstancesUtil
Compares two instances, ignoring the class attribute (if any)
equals(Object) - Method in class weka.classifiers.misc.monotone.Coordinates
Indicates if the object o equals this.
equals(Object) - Method in class weka.classifiers.misc.monotone.CumulativeDiscreteDistribution
Indicates if the object o equals this.

G

generateRandomSample(Instances, int, Random) - Static method in class weka.classifiers.misc.monotone.InstancesUtil
Generates a random sample of instances.
get(int, int) - Method in interface weka.classifiers.misc.monotone.BitMatrix
Return the element a the specified position.
get(int, int) - Method in class weka.classifiers.misc.monotone.BooleanBitMatrix
Returns the element a the specified position.
getBalanced() - Method in class weka.classifiers.misc.monotone.OSDLCore
Returns if the balanced version of OSDL is in effect.
getBitMatrix(Instances) - Static method in class weka.classifiers.misc.monotone.InstancesUtil
Calculates the relation (poset) formed by the instances.
getCapabilities() - Method in class weka.classifiers.misc.monotone.OSDLCore
Returns default capabilities of the classifier.
getClassificationType() - Method in class weka.classifiers.misc.monotone.OSDLCore
Returns the classification type.
getCumulativeProbability(int) - Method in class weka.classifiers.misc.monotone.CumulativeDiscreteDistribution
Get the probability of finding an element smaller or equal than index.
getDistributionArray(DiscreteEstimator) - Static method in class weka.classifiers.misc.monotone.DistributionUtils
Converts a DiscreteEstimator to an array of doubles.
getInterpolationParameter() - Method in class weka.classifiers.misc.monotone.OSDLCore
Returns the current value of the interpolation parameter.
getInterpolationParameterLowerBound() - Method in class weka.classifiers.misc.monotone.OSDLCore
Returns the lower bound for the interpolation parameter tuning (0 <= x < 1).
getInterpolationParameterUpperBound() - Method in class weka.classifiers.misc.monotone.OSDLCore
Returns the upper bound for the interpolation parameter tuning (0 < x <= 1).
getLowerBound() - Method in class weka.classifiers.misc.monotone.OSDLCore
Returns the current value of the lower bound for the interpolation parameter.
getMaximalCumulativeDiscreteDistribution(int) - Static method in class weka.classifiers.misc.monotone.DistributionUtils
Get the maximal CumulativeDiscreteDistribution over numClasses elements.
getMinimalCumulativeDiscreteDistribution(int) - Static method in class weka.classifiers.misc.monotone.DistributionUtils
Get the minimal CumulativeDiscreteDistribution over numClasses elements.
getNumberOfPartsForInterpolationParameter() - Method in class weka.classifiers.misc.monotone.OSDLCore
Gets the granularity for tuning the interpolation parameter.
getNumInstances() - Method in class weka.classifiers.misc.monotone.OSDLCore
Returns the number of instances in the training set.
getNumSymbols() - Method in class weka.classifiers.misc.monotone.CumulativeDiscreteDistribution
Get the number of elements over which the cumulative probability distribution is defined.
getNumSymbols() - Method in class weka.classifiers.misc.monotone.DiscreteDistribution
Get the number of elements over which the DiscreteDistribution is defined.
getOptions() - Method in class weka.classifiers.misc.monotone.OSDLCore
Gets the current settings of the OSDLCore classifier.
getProbability(int) - Method in class weka.classifiers.misc.monotone.DiscreteDistribution
Get the probability of finding the element at a specified index.
getRevision() - Method in class weka.classifiers.misc.monotone.AbsoluteLossFunction
Returns the revision string.
getRevision() - Method in class weka.classifiers.misc.monotone.BooleanBitMatrix
Returns the revision string.
getRevision() - Method in class weka.classifiers.misc.monotone.Coordinates
Returns the revision string.
getRevision() - Method in class weka.classifiers.misc.monotone.CumulativeDiscreteDistribution
Returns the revision string.
getRevision() - Method in class weka.classifiers.misc.monotone.DiscreteDistribution
Returns the revision string.
getRevision() - Method in class weka.classifiers.misc.monotone.DistributionUtils
Returns the revision string.
getRevision() - Method in class weka.classifiers.misc.monotone.EnumerationIterator
Returns the revision string.
getRevision() - Method in class weka.classifiers.misc.monotone.InstancesComparator
Returns the revision string.
getRevision() - Method in class weka.classifiers.misc.monotone.InstancesUtil
Returns the revision string.
getRevision() - Method in class weka.classifiers.misc.monotone.MultiDimensionalSort
Returns the revision string.
getRevision() - Method in class weka.classifiers.misc.monotone.ZeroOneLossFunction
Returns the revision string.
getRevision() - Method in class weka.classifiers.misc.OSDL
Returns the revision string.
getTechnicalInformation() - Method in class weka.classifiers.misc.monotone.OSDLCore
Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.
getTuneInterpolationParameter() - Method in class weka.classifiers.misc.monotone.OSDLCore
Returns whether the interpolation parameter is to be tuned based on the bounds.
getUpperBound() - Method in class weka.classifiers.misc.monotone.OSDLCore
Returns the current value of the upper bound for the interpolation parameter.
getValue(int) - Method in class weka.classifiers.misc.monotone.Coordinates
Get the value of the attribute with index index, ignoring the class attribute.
getValues(double[]) - Method in class weka.classifiers.misc.monotone.Coordinates
Get the values of the coordinates.
getWeighted() - Method in class weka.classifiers.misc.monotone.OSDLCore
Returns if the weighted version is in effect.
globalInfo() - Method in class weka.classifiers.misc.monotone.OSDLCore
Returns a string describing the classifier.

H

hashCode() - Method in class weka.classifiers.misc.monotone.Coordinates
Gets the hash code value for this object.
hasNext() - Method in class weka.classifiers.misc.monotone.EnumerationIterator
Returns true if there are more elements in the iteration.

I

InstancesComparator - Class in weka.classifiers.misc.monotone
Class to compare instances with respect to a given attribute, indicated by its index.
InstancesComparator(int) - Constructor for class weka.classifiers.misc.monotone.InstancesComparator
Construct an InstancesComparator that compares the attributes with the given index.
InstancesComparator(int, boolean) - Constructor for class weka.classifiers.misc.monotone.InstancesComparator
Construct an InstancesComparator that compares the attributes with the given index, with the possibility of reversing the order.
InstancesUtil - Class in weka.classifiers.misc.monotone
This class contains some methods for working with objects of type Instance and Instances, not provided by there respective classes.
InstancesUtil() - Constructor for class weka.classifiers.misc.monotone.InstancesUtil
 
interpolate(CumulativeDiscreteDistribution, CumulativeDiscreteDistribution, double) - Static method in class weka.classifiers.misc.monotone.DistributionUtils
Compute a linear interpolation between the two given CumulativeDiscreteDistribution.
interpolate(CumulativeDiscreteDistribution, CumulativeDiscreteDistribution, double[]) - Static method in class weka.classifiers.misc.monotone.DistributionUtils
Compute a linear interpolation between the two given CumulativeDiscreteDistribution.
interpolate(DiscreteDistribution, DiscreteDistribution, double) - Static method in class weka.classifiers.misc.monotone.DistributionUtils
Compute a linear interpolation between the two given DiscreteDistribution.
interpolationParameterLowerBoundTipText() - Method in class weka.classifiers.misc.monotone.OSDLCore
Returns the tip text for this property.
interpolationParameterTipText() - Method in class weka.classifiers.misc.monotone.OSDLCore
Returns the tip text for this property.
interpolationParameterUpperBoundTipText() - Method in class weka.classifiers.misc.monotone.OSDLCore
Returns the tip text for this property.
isHomogeneous(Instances) - Static method in class weka.classifiers.misc.monotone.InstancesUtil
Check if all instances have the same class value.
isMonotone(Instances) - Static method in class weka.classifiers.misc.monotone.InstancesUtil
Checks if the given data set is monotone.
isQuasiMonotone(Instances, Instances) - Static method in class weka.classifiers.misc.monotone.InstancesUtil
Test if a set of instances is quasi monotone.

L

listOptions() - Method in class weka.classifiers.misc.monotone.OSDLCore
Returns an enumeration describing the available options.
loss(double, double) - Method in class weka.classifiers.misc.monotone.AbsoluteLossFunction
Returns the absolute loss function between two class values.
loss(double, double) - Method in interface weka.classifiers.misc.monotone.NominalLossFunction
Calculate the loss between an actual and a predicted class value.
loss(double, double) - Method in class weka.classifiers.misc.monotone.ZeroOneLossFunction
Returns the zero-one loss function between two class values.

M

main(String[]) - Static method in class weka.classifiers.misc.OSDL
Main method for testing this class and for using it from the command line.
maximalExtension(Instances, Instance) - Static method in class weka.classifiers.misc.monotone.InstancesUtil
Computes the maximal extension for a given instance.
maximalExtension(Instances, Instance, double) - Static method in class weka.classifiers.misc.monotone.InstancesUtil
Computes the maximal extension of a given instance, but the maximal value returned is maxValue.
mean() - Method in class weka.classifiers.misc.monotone.DiscreteDistribution
Calculate the mean of the distribution.
median() - Method in class weka.classifiers.misc.monotone.DiscreteDistribution
Calculate the median of the distribution.
minimalExtension(Instances, Instance) - Static method in class weka.classifiers.misc.monotone.InstancesUtil
Computes the minimal extension for a given instance.
minimalExtension(Instances, Instance, double) - Static method in class weka.classifiers.misc.monotone.InstancesUtil
Computes the minimal extension of a given instance, but the minimal value returned is minValue.
modes() - Method in class weka.classifiers.misc.monotone.DiscreteDistribution
Get a sorted array containing the indices of the elements with maximal probability.
MultiDimensionalSort - Class in weka.classifiers.misc.monotone
Class for doing multidimensional sorting, using an array of Comparator.
MultiDimensionalSort() - Constructor for class weka.classifiers.misc.monotone.MultiDimensionalSort
 
multiDimensionalSort(Object[], Comparator[]) - Static method in class weka.classifiers.misc.monotone.MultiDimensionalSort
Sort an array using different comparators.
multiDimensionalSort(Object[], int, int, Comparator[]) - Static method in class weka.classifiers.misc.monotone.MultiDimensionalSort
Sort part of an array using different comparators.

N

next() - Method in class weka.classifiers.misc.monotone.EnumerationIterator
Returns the next element in the iteration.
nextOccurenceIgnoreClass(Instances, Instance, int) - Static method in class weka.classifiers.misc.monotone.InstancesUtil
Find the next occurence of an instance, ignoring the class, for which the index in the dataset is at least index.
NominalLossFunction - Interface in weka.classifiers.misc.monotone
Interface for incorporating different loss functions.
nrOfRedundant(Instances) - Static method in class weka.classifiers.misc.monotone.InstancesUtil
Counts the number of redundant pairs in the sense of OLM.
nrOfReversedPreferences(Instances) - Static method in class weka.classifiers.misc.monotone.InstancesUtil
Gather some statistics regarding reversed preferences.
nrStochasticReversedPreference(Instances) - Static method in class weka.classifiers.misc.monotone.InstancesUtil
Find the number of stochastic reversed preferences in the dataset.
numberInInterval(Instance, Instance) - Static method in class weka.classifiers.misc.monotone.InstancesUtil
Calculatus the number of elements in the closed interval [low,up].
numberOfGreaterVectors(Instance) - Static method in class weka.classifiers.misc.monotone.InstancesUtil
Calculatutes the number of vectors in the data space that are greater or equal than the given instance.
numberOfPartsForInterpolationParameterTipText() - Method in class weka.classifiers.misc.monotone.OSDLCore
Returns the tip text for this property.
numberOfSmallerVectors(Instance) - Static method in class weka.classifiers.misc.monotone.InstancesUtil
Calculatutes the number of vectors in the data space that are smaller or equal than the given instance.

O

OSDL - Class in weka.classifiers.misc
This class is an implementation of the Ordinal Stochastic Dominance Learner.
Further information regarding the OSDL-algorithm can be found in:

S.
OSDL() - Constructor for class weka.classifiers.misc.OSDL
 
OSDLCore - Class in weka.classifiers.misc.monotone
This class is an implementation of the Ordinal Stochastic Dominance Learner.
Further information regarding the OSDL-algorithm can be found in:

S.
OSDLCore() - Constructor for class weka.classifiers.misc.monotone.OSDLCore
 

R

remove() - Method in class weka.classifiers.misc.monotone.EnumerationIterator
Since the iteration is based on an enumeration, removal of elements is not supported.
reversedPreference(Instance, Instance) - Static method in class weka.classifiers.misc.monotone.InstancesUtil
Checks if two instances give rise to reversed preference.
rowCount(int) - Method in interface weka.classifiers.misc.monotone.BitMatrix
Counts the number of bits that are set in the specified row.
rowCount(int) - Method in class weka.classifiers.misc.monotone.BooleanBitMatrix
Counts the number of bits that are set in the specified row.
rows() - Method in interface weka.classifiers.misc.monotone.BitMatrix
Gets the number of rows.
rows() - Method in class weka.classifiers.misc.monotone.BooleanBitMatrix
Gets the number of rows.

S

sampleWithoutReplacement(Instances, int, Random) - Static method in class weka.classifiers.misc.monotone.InstancesUtil
Create, without replacement, a random subsample of the given size from the given instances.
set(int, int, boolean) - Method in interface weka.classifiers.misc.monotone.BitMatrix
Sets the bit at the specified position to the specified value.
set(int, int) - Method in interface weka.classifiers.misc.monotone.BitMatrix
Sets the bit at the specified position to true.
set(int, int, boolean) - Method in class weka.classifiers.misc.monotone.BooleanBitMatrix
Sets the bit at the specified position to the specified value.
set(int, int) - Method in class weka.classifiers.misc.monotone.BooleanBitMatrix
Sets the bit at the specified position to true.
setBalanced(boolean) - Method in class weka.classifiers.misc.monotone.OSDLCore
If balanced is true then the balanced version of OSDL will be used, otherwise the ordinary version of OSDL will be in effect.
setClassificationType(SelectedTag) - Method in class weka.classifiers.misc.monotone.OSDLCore
Sets the classification type.
setInterpolationParameter(double) - Method in class weka.classifiers.misc.monotone.OSDLCore
Sets the interpolation parameter.
setInterpolationParameterBounds(double, double) - Method in class weka.classifiers.misc.monotone.OSDLCore
Sets the interpolation bounds for the interpolation parameter.
setInterpolationParameterLowerBound(double) - Method in class weka.classifiers.misc.monotone.OSDLCore
Sets the lower bound for the interpolation parameter tuning (0 <= x < 1).
setInterpolationParameterUpperBound(double) - Method in class weka.classifiers.misc.monotone.OSDLCore
Sets the upper bound for the interpolation parameter tuning (0 < x <= 1).
setNumberOfPartsForInterpolationParameter(int) - Method in class weka.classifiers.misc.monotone.OSDLCore
Sets the granularity for tuning the interpolation parameter.
setOptions(String[]) - Method in class weka.classifiers.misc.monotone.OSDLCore
Parses the options for this object.
setTuneInterpolationParameter(boolean) - Method in class weka.classifiers.misc.monotone.OSDLCore
Sets whether the interpolation parameter is to be tuned based on the bounds.
setWeighted(boolean) - Method in class weka.classifiers.misc.monotone.OSDLCore
If weighted is true then the weighted version of the OSDL is used.
smallerOrEqual(Coordinates) - Method in class weka.classifiers.misc.monotone.Coordinates
Checks if this is smaller or equal than cc.
smallerOrEqual(Instance, Instance) - Static method in class weka.classifiers.misc.monotone.InstancesUtil
Compares two instances in the data space, this is, ignoring the class attribute.
stochasticDominatedBy(CumulativeDiscreteDistribution) - Method in class weka.classifiers.misc.monotone.CumulativeDiscreteDistribution
Returns if this is dominated by cdf.
stochasticDominatedBy(DiscreteDistribution) - Method in class weka.classifiers.misc.monotone.DiscreteDistribution
Checks if this is dominated by dd.
strictlySmaller(Coordinates) - Method in class weka.classifiers.misc.monotone.Coordinates
Checks if this is strictly smaller than cc.
strictlySmaller(Instance, Instance) - Static method in class weka.classifiers.misc.monotone.InstancesUtil
Compares two instances in the data space, this is ignoring the class attribute.

T

TAGS_CLASSIFICATIONTYPES - Static variable in class weka.classifiers.misc.monotone.OSDLCore
the classification types
takeMax(CumulativeDiscreteDistribution, CumulativeDiscreteDistribution) - Static method in class weka.classifiers.misc.monotone.DistributionUtils
Create a new CumulativeDiscreteDistribution that is the maximum of the two given CumulativeDiscreteDistribution.
takeMin(CumulativeDiscreteDistribution, CumulativeDiscreteDistribution) - Static method in class weka.classifiers.misc.monotone.DistributionUtils
Create a new CumulativeDiscreteDistribution that is the minimum of the two given CumulativeDiscreteDistribution.
toArray() - Method in class weka.classifiers.misc.monotone.CumulativeDiscreteDistribution
Get an array representation of the cumulative probability distribution.
toArray() - Method in class weka.classifiers.misc.monotone.DiscreteDistribution
Convert the DiscreteDistribution to an array of doubles.
toDataDouble(Instance) - Static method in class weka.classifiers.misc.monotone.InstancesUtil
Returns an array containing the attribute values (in internal floating point format) of the given instance in data space, this is, the class attribute (if any) is removed.
toString() - Method in class weka.classifiers.misc.monotone.AbsoluteLossFunction
Returns a string with the name of the loss function.
toString() - Method in class weka.classifiers.misc.monotone.BooleanBitMatrix
Create a compact string representation of the matrix.
toString() - Method in class weka.classifiers.misc.monotone.Coordinates
Get a string representation of this object.
toString() - Method in class weka.classifiers.misc.monotone.CumulativeDiscreteDistribution
Get a string representation of the cumulative probability distribution.
toString() - Method in class weka.classifiers.misc.monotone.DiscreteDistribution
Get a string representation of the given DiscreteDistribution.
toString() - Method in class weka.classifiers.misc.monotone.OSDLCore
Returns a description of the classifier.
toString() - Method in class weka.classifiers.misc.monotone.ZeroOneLossFunction
Returns a string with the name of the loss function.
totalLoss(Classifier, Instances, NominalLossFunction) - Static method in class weka.classifiers.misc.monotone.InstancesUtil
Calulates the total loss over the instances , using the trained classifier and the specified lossFunction.
transpose() - Method in class weka.classifiers.misc.monotone.BooleanBitMatrix
Swap the rows and the columns of the BooleanBitMatrix.
transposeInPlace() - Method in class weka.classifiers.misc.monotone.BooleanBitMatrix
Swaps the rows and the columns of the BooleanBitMatrix, without creating a new object.
tuneInterpolationParameter() - Method in class weka.classifiers.misc.monotone.OSDLCore
Tune the interpolation parameter using the current settings of the classifier.
tuneInterpolationParameter(double, double, int, int) - Method in class weka.classifiers.misc.monotone.OSDLCore
Tunes the interpolation parameter using the given settings.
tuneInterpolationParameterTipText() - Method in class weka.classifiers.misc.monotone.OSDLCore
Returns the tip text for this property.

W

weightedTipText() - Method in class weka.classifiers.misc.monotone.OSDLCore
Returns a string suitable for displaying in the gui/experimenter.
weka.classifiers.misc - package weka.classifiers.misc
 
weka.classifiers.misc.monotone - package weka.classifiers.misc.monotone
 
write(Instances, BufferedWriter) - Static method in class weka.classifiers.misc.monotone.InstancesUtil
Write the instances in ARFF-format to the indicated BufferedWriter .

Z

ZeroOneLossFunction - Class in weka.classifiers.misc.monotone
Class implementing the zero-one loss function, this is an incorrect prediction always accounts for one unit loss.
ZeroOneLossFunction() - Constructor for class weka.classifiers.misc.monotone.ZeroOneLossFunction
 

A B C D E G H I L M N O R S T W Z