IFPD confirmation measures are used in ranking inductive rules in Data Mining. Many measures of this kind have been defined in literature. We show how some of them are related to each other via weighted means. The special structure of IFPD measures allows to define also new monotonicity and symmetry properties which appear quite natural in such context. We also suggest a way to measure the degree of symmetry of IFPD confirmation measures.

Monotonicity and Symmetry of IFPD Bayesian Confirmation Measures

CELOTTO, EMILIO;ELLERO, Andrea;FERRETTI, Paola
2016-01-01

Abstract

IFPD confirmation measures are used in ranking inductive rules in Data Mining. Many measures of this kind have been defined in literature. We show how some of them are related to each other via weighted means. The special structure of IFPD measures allows to define also new monotonicity and symmetry properties which appear quite natural in such context. We also suggest a way to measure the degree of symmetry of IFPD confirmation measures.
2016
Modeling Decisions for Artificial Intelligence: 13th International Conference, MDAI 2016, Sant Julià de Lòria, Andorra, September 19-21, 2016
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/10278/3678864
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