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stať ve sborníku (D)
Home Department:
Ústav pro výzkum a aplikace fuzzy modelování (94410)
Title:
Discovering Fuzzy and Statistical Patterns in Data: The nuggets R Package
Citace
Burda, M. Discovering Fuzzy and Statistical Patterns in Data: The nuggets R Package.
In:
The Eighteenth International Conference on Fuzzy Set Theory and Applications: Proceedings of The Eighteenth International Conference on Fuzzy Set Theory and Applications 2026-01-25 Liptovský Ján.
Ostrava: Ostravská univerzita, 2026. s. 29-32. ISBN 978-80-7599-515-5.
Subtitle
Publication year:
2026
Obor:
Number of pages:
4
Page from:
29
Page to:
32
Form of publication:
Elektronická verze
ISBN code:
978-80-7599-515-5
ISSN code:
Proceedings title:
Proceedings of The Eighteenth International Conference on Fuzzy Set Theory and Applications
Proceedings:
Mezinárodní
Publisher name:
Ostravská univerzita
Place of publishing:
Ostrava
Country of Publication:
Sborník vydaný v ČR
Název konference:
The Eighteenth International Conference on Fuzzy Set Theory and Applications
Conference venue:
Liptovský Ján
Datum zahájení konference:
Typ akce podle státní
příslušnosti účastníků:
Celosvětová akce
WoS code:
EID:
Key words in English:
association rules; R package; fuzzy rules
Annotation in original language:
The nuggets package provides a flexible and extensible frame-work for discovering interpretable data patterns based on frequent logical conditions. Its designunifies classical association-rule mining with linguistic and fuzzy representations, while enablingoptional statistical evaluation for selected pattern types such as conditional contrasts and corre-lations. Pattern generation is driven by support, ensuring efficient mining of relevant conditions,whereas additional quantitative analyses or tests can be seamlessly attached when desired.A major strength of nuggets lies in its extensibility. The framework allows users to definecustom fuzzification schemes and to evaluate an arbitrary R function on every frequent con-dition, thereby enabling the creation of new, user-defined pattern types. This design encour-ages experimentation with alternative logical semantics, statistical measures, and application-specific evaluation criteria, making nuggets not only a tool for applied pattern discovery butalso a research platform for developing new methods.
Annotation in english language:
The nuggets package provides a flexible and extensible frame-work for discovering interpretable data patterns based on frequent logical conditions. Its designunifies classical association-rule mining with linguistic and fuzzy representations, while enablingoptional statistical evaluation for selected pattern types such as conditional contrasts and corre-lations. Pattern generation is driven by support, ensuring efficient mining of relevant conditions,whereas additional quantitative analyses or tests can be seamlessly attached when desired.A major strength of nuggets lies in its extensibility. The framework allows users to definecustom fuzzification schemes and to evaluate an arbitrary R function on every frequent con-dition, thereby enabling the creation of new, user-defined pattern types. This design encour-ages experimentation with alternative logical semantics, statistical measures, and application-specific evaluation criteria, making nuggets not only a tool for applied pattern discovery butalso a research platform for developing new methods.
References
Reference
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