| weka.classifiers.misc.monotone |
|
| Java Source File Name | Type | Comment |
| AbsoluteLossFunction.java | Class | Class implementing the absolute loss function, this means
the returned loss is the abolute value of the difference
between the predicted and actual value.
This implementation is done as part of the master's thesis: "Studie
en implementatie van instantie-gebaseerde algoritmen voor gesuperviseerd
rangschikken", Stijn Lievens, Ghent University, 2004. |
| BitMatrix.java | Interface | Interface specifying a simple matrix of booleans. |
| BooleanBitMatrix.java | Class | This class is a very simple implementation of a BitMatrix.
In fact, it uses a two-dimensional array of booleans, so it is
not very space efficient.
This implementation is part of the master's thesis: "Studie
en implementatie van instantie-gebaseerde algoritmen voor gesuperviseerd
rangschikken", Stijn Lievens, Ghent University, 2004. |
| Coordinates.java | Class | This is a simple implementation of the data space. |
| CumulativeDiscreteDistribution.java | Class | Represents a discrete cumulative probability distribution
over a totally ordered discrete set. |
| DiscreteDistribution.java | Class | This class represents a discrete probability distribution
over a finite number of values.
In the present implementation, objects of type
DiscreteDistribution are in fact immutable,
so all one can do is create objects and retrieve information,
such as median and mean, from them.
This implementation is part of the master's thesis: "Studie
en implementatie van instantie-gebaseerde algoritmen voor gesuperviseerd
rangschikken", Stijn Lievens, Ghent University, 2004. |
| DistributionUtils.java | Class | Class with some simple methods acting on
CumulativeDiscreteDistribution. |
| EnumerationIterator.java | Class | Implementation of a simple wrapper class for the Enumeration
interface.
This makes it possible to use an Enumeration as if
it were an Iterator. |
| InstancesComparator.java | Class | Class to compare instances with respect to a given attribute, indicated
by its index. |
| InstancesUtil.java | Class | This class contains some methods for working with objects of
type Instance and Instances, not
provided by there respective classes.
This implementation is part of the master's thesis: "Studie
en implementatie van instantie-gebaseerde algoritmen voor gesuperviseerd
rangschikken", Stijn Lievens, Ghent University, 2004. |
| MultiDimensionalSort.java | Class | Class for doing multidimensional sorting, using an array of
Comparator. |
| NominalLossFunction.java | Interface | Interface for incorporating different loss functions.
This interface contains only one method, namely loss
that measures the error between an actual class
value actual and a predicted value
predicted. |
| OSDLCore.java | Class |
This class is an implementation of the Ordinal Stochastic Dominance Learner.
Further information regarding the OSDL-algorithm can be found in:
S. |
| ZeroOneLossFunction.java | Class | Class implementing the zero-one loss function, this is
an incorrect prediction always accounts for one unit loss.
This implementation is done as part of the master's thesis: "Studie
en implementatie van instantie-gebaseerde algoritmen voor gesuperviseerd
rangschikken", Stijn Lievens, Ghent University, 2004. |