Name
Title | ||
|---|---|---|
An Extension of Totohasina's Normalization Theory of Quality Measures of Association Rules. |
Abstract | ||
|---|---|---|
In the context of binary data mining, for unifying view on probabilistic quality measures of association rules, Totohasina’s theory of normalization of quality measures of association rules primarily based on affine homeomorphism presents some drawbacks. Indeed, it cannot normalize some interestingness measures which are explained below. This paper presents an extension of it, as a new normalization method based on proper homographic homeomorphism that appears most consequent. |
Year | DOI | Venue |
|---|---|---|
2019 | 10.1155/2019/7829805 | Int. J. Math. Mathematical Sciences |
Field | DocType | Volume |
Affine transformation,Topology,Normalization (statistics),Theoretical computer science,Correlation and dependence,Binary data,Probabilistic logic,Mathematics,Homeomorphism | Journal | 2019 |
Citations | PageRank | References |
0 | 0.34 | 0 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Armand Armand | 1 | 0 | 0.68 |
| André Totohasina | 2 | 3 | 1.82 |
| Daniel R. Feno | 3 | 1 | 1.03 |