Dependence Factor as a Rule Evaluation Measure
AbstractCertainty factor and lift are known evaluation measures of association rules. Nevertheless, they do not guarantee accurate evaluation of the strength of dependence between rule’s constituents. In particular, even if there is a strongest possible positive or negative dependence between rule’s constituents X and Y, these measures may reach values quite close to the values indicating independence of X and Y. Recently, we have proposed a new measure called a dependence factor to overcome this drawback. Unlike in the case of the certainty factor, when defining the dependence factor, we took into account the fact that for a given rule X→Y , the minimal conditional probability of the occurrence of Y given X may be greater than 0, while its maximal possible value may less than 1. In this paper, we first recall definitions and properties of all the three measures. Then, we examine the dependence factor from the point of view of an interestingness measure as well as we examine the relationship among the dependence factor for X and Y with those for X ¯ and Y, X and Y ¯ , as well as X ¯ and Y ¯ , respectively. As a result, we obtain a number of new properties of the dependence factor.
|Publication size in sheets||0.9|
Matwin Stan, Mielniczuk Jan (eds.): Challenges in Computational Statistics and Data Mining, Studies in Computational Intelligence, vol. 605, 2016, Heidelberg New York Dordrecht London, Springer International Publishing, ISBN 978-3-319-18780-8, [978-3-319-18781-5], 399 p., DOI:10.1007/978-3-319-18781-5
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|Project||Development of new algorithms in the areas of software and computer architecture, artificial intelligence and information systems and computer graphics . Project leader: Rybiński Henryk,
, Phone: +48 22 234 7731, start date 18-05-2015, end date 30-11-2016, II/2015/DS/1, Completed
|Score||= 5.0, 01-02-2020, MonographChapterAuthor|
|Publication indicators||= 3; = 1; = 2.0; : 2016 = 0.39|
|Citation count*||2 (2020-09-06)|
* presented citation count is obtained through Internet information analysis and it is close to the number calculated by the Publish or Perish system.