Name
Abstract | ||
|---|---|---|
Mining emerging patterns aims at contrasting data sets and identifying itemsets that characterise a data set by contrast to a reference data set, so as to capture and highlight their differences. This paper considers the case of emerging gradual patterns, to extract discriminant attribute co-variations. It discusses the specific features of these gradual patterns and proposes to transpose an efficient border-based algorithm, justifying its applicability to the gradual case. Illustrative results obtained from a UCI data set are described. |
Year | Venue | Keywords |
|---|---|---|
2015 | PROCEEDINGS OF THE 2015 CONFERENCE OF THE INTERNATIONAL FUZZY SYSTEMS ASSOCIATION AND THE EUROPEAN SOCIETY FOR FUZZY LOGIC AND TECHNOLOGY | Gradual Patterns,Emerging Patterns,Discriminant Characterisation |
Field | DocType | Volume |
Reference data (financial markets),Data mining,Data set,Transpose,Computer science,Discriminant | Conference | 89 |
ISSN | Citations | PageRank |
1951-6851 | 0 | 0.34 |
References | Authors | |
14 | 3 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Anne Laurent | 1 | 244 | 38.13 |
| Marie-Jeanne Lesot | 2 | 220 | 32.41 |
| Maria Rifqi | 3 | 407 | 33.64 |