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BitMatrix
with the indicated
number of rows and columns.
Coordinates
for the given instance.
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.
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.
Enumeration
interface. 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.
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.
true
if there are more elements in the iteration.
InstancesComparator
that compares
the attributes with the given index.
InstancesComparator
that compares
the attributes with the given index, with the possibility of
reversing the order.
Instance
and Instances,
not
provided by there respective classes. 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.
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.
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.
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.
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.
BufferedWriter
.
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