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## Package weka.classifiers.misc.monotone

Interface Summary
BitMatrix | Interface specifying a simple matrix of booleans.
NominalLossFunction | Interface for incorporating different loss functions.

Class Summary
AbsoluteLossFunction | Class implementing the absolute loss function, this means the returned loss is the abolute value of the difference between the predicted and actual value.
BooleanBitMatrix | This class is a very simple implementation of a BitMatrix.
Coordinates | This is a simple implementation of the data space.
CumulativeDiscreteDistribution | Represents a discrete cumulative probability distribution over a totally ordered discrete set.
DiscreteDistribution | This class represents a discrete probability distribution over a finite number of values.
DistributionUtils | Class with some simple methods acting on `CumulativeDiscreteDistribution.`
EnumerationIterator | Implementation of a simple wrapper class for the `Enumeration` interface.
InstancesComparator | Class to compare instances with respect to a given attribute, indicated by its index.
InstancesUtil | This class contains some methods for working with objects of type `Instance` and `Instances,` not provided by there respective classes.
MultiDimensionalSort | Class for doing multidimensional sorting, using an array of `Comparator.`
OSDLCore | This class is an implementation of the Ordinal Stochastic Dominance Learner. Further information regarding the OSDL-algorithm can be found in: S.
ZeroOneLossFunction | Class implementing the zero-one loss function, this is an incorrect prediction always accounts for one unit loss.

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