OLM
Package
weka.classifiers.misc
Synopsis
This class is an implementation of the Ordinal Learning Method
Further information regarding the algorithm and variants can be found in:
Arie Ben-David (1992). Automatic Generation of Symbolic Multiattribute Ordinal Knowledge-Based DSSs: methodology and Applications. Decision Sciences. 23:1357-1372.
Lievens, Stijn (2003-2004). Studie en implementatie van instantie-gebaseerde algoritmen voor gesuperviseerd rangschikken..
Options
The table below describes the options available for OLM.
Option |
Description |
|---|---|
averagingType |
Choses the way in which the distributions are averaged in the first phase of the algorithm. |
classificationType |
Sets the classification type. |
debug |
If set to true, classifier may output additional info to the console. |
distanceType |
Sets the distance that is to be used by the nearest neighbour rule |
extensionType |
Sets the extension type to use. |
seed |
Sets the seed that is used to randomize the instances prior to building the rule bases |
sort |
If true, the instances are also sorted within the classes prior to building the rule bases. |
Capabilities
The table below describes the capabilites of OLM.
Capability |
Supported |
|---|---|
Class |
Missing class values, Binary class, Nominal class |
Attributes |
Nominal attributes, Unary attributes, Binary attributes, Empty nominal attributes |
Min # of instances |
0 |