International Journal of Computational Intelligence Systems

Volume 1, Issue 1, January 2008, Pages 1 - 18

Some Measures Relating Partitions Useful for Computational Intelligence

Authors
Ronald R. Yager
Corresponding Author
Ronald R. Yager
Available Online 10 February 2008.
DOI
https://doi.org/10.2991/ijcis.2008.1.1.1How to use a DOI?
Abstract
SOME MEASURES RELATING PARTITIONS USEFUL FOR COMPUTATIONAL INTELLIGENCE We investigate a number of measures relating partitions. One class of measures we consider are congru- ence measures. These measures are used to calculate the similarity between two partitionings. We provide a number of examples of this type of measure. Another class of measures we investigate are prognosti- cation measures. This type of measure, closely related to a concept of containment between partitions, is useful in indicating how well knowledge of an objects class in one partitioning indicates its class in a second partitioning. We apply our measures to some data mining applications. One example is in choos- ing the appropriate level of a concept hierarchy. We also introduce a measure of the non-specificity of a partition. This measures a feature of a partition related to the granularity of the constituent classes of the partition.
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Journal
International Journal of Computational Intelligence Systems
Volume-Issue
1 - 1
Pages
1 - 18
Publication Date
2008/02
ISSN (Online)
1875-6883
ISSN (Print)
1875-6891
DOI
https://doi.org/10.2991/ijcis.2008.1.1.1How to use a DOI?
Open Access
This is an open access article distributed under the CC BY-NC license.

Cite this article

TY  - JOUR
AU  - Ronald R. Yager
PY  - 2008
DA  - 2008/02
TI  - Some Measures Relating Partitions Useful for Computational Intelligence
JO  - International Journal of Computational Intelligence Systems
SP  - 1
EP  - 18
VL  - 1
IS  - 1
SN  - 1875-6883
UR  - https://doi.org/10.2991/ijcis.2008.1.1.1
DO  - https://doi.org/10.2991/ijcis.2008.1.1.1
ID  - Yager2008
ER  -