Paper Info
Title
Analysis of symmetry properties for bayesian confirmation measures
Abstract
The paper considers symmetry properties of Bayesian confirmation measures, which constitute an important group of interestingness measures for evaluation of rules induced from data. We demonstrate that the symmetry properties proposed in the literature do not fully reflect the concept of confirmation. We conduct a thorough analysis of the symmetries regarding that the confirmation should express how much more probable the rule's hypothesis is when the premise is present rather than when the premise is absent. As a result we point out which symmetries are desired for Bayesian confirmation measures and which are truly unattractive. Such knowledge is a valuable tools for assessing the quality and usefulness of measures.
Year
DOI
Venue
2012
10.1007/978-3-642-31900-6_27
RSKT
Keywords
Field
DocType
important group,bayesian confirmation measure,interestingness measure,valuable tool,symmetry property,thorough analysis,business information systems,computing
Management information systems,Computer science,Premise,Artificial intelligence,Machine learning,Bayesian probability
Conference
Citations 
PageRank 
References 
8
0.60
9
Authors
3
Name
Order
Citations
PageRank
Salvatore Greco13977266.79
Roman Slowinski25561516.06
Izabela Szczęch3567.90