OSDL
Package
weka.classifiers.misc
Synopsis
This class is an implementation of the Ordinal Stochastic Dominance Learner.
Further information regarding the OSDL-algorithm can be found in:
S. Lievens, B. De Baets, K. Cao-Van (2006). A Probabilistic Framework for the Design of Instance-Based Supervised Ranking Algorithms in an Ordinal Setting. Annals of Operations Research..
Kim Cao-Van (2003). Supervised ranking: from semantics to algorithms.
Stijn Lievens (2004). Studie en implementatie van instantie-gebaseerde algoritmen voor gesuperviseerd rangschikken.
For more information about supervised ranking, see
http://users.ugent.be/~slievens/supervised_ranking.php
Options
The table below describes the options available for OSDL.
Option |
Description |
|---|---|
balanced |
If true, the balanced version of the OSDL-algorithm is used |
classificationType |
Sets the way in which a single label will be extracted from the estimated distribution. |
debug |
If set to true, classifier may output additional info to the console. |
interpolationParameter |
Sets the value of the interpolation parameter s;Estimated distribution is s * f_min + (1 - s) * f_max. |
interpolationParameterLowerBound |
Sets the lower bound for the interpolation parameter tuning (0 <= x < 1). |
interpolationParameterUpperBound |
Sets the upper bound for the interpolation parameter tuning (0 < x <= 1). |
numberOfPartsForInterpolationParameter |
Sets the granularity for tuning the interpolation parameter; For instance if the value is 32 then 33 values for the interpolation are checked. |
tuneInterpolationParameter |
Whether to tune the interpolation parameter based on the bounds. |
weighted |
If true, the weighted version of the OSDL-algorithm is used |
Capabilities
The table below describes the capabilites of OSDL.
Capability |
Supported |
|---|---|
Class |
Binary class, Nominal class, Missing class values |
Attributes |
Unary attributes, Empty nominal attributes, Nominal attributes, Binary attributes |
Min # of instances |
0 |