Volume 1, Issue 1, January 2008, Pages 1 - 18
Some Measures Relating Partitions Useful for Computational Intelligence
Ronald R. Yager
Ronald R. Yager
Received 13 October 2007, Revised 6 November 2007, Available Online 1 January 2008.
- https://doi.org/10.2991/ijcis.2008.1.1.1How to use a DOI?
- 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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Cite this article
TY - JOUR AU - Ronald R. Yager PY - 2008 DA - 2008/01 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 -