OSACA: Discovering Ordinal Categorical Attributes

Autor: Marsala, Christophe, Laurent, Anne, Lesot, Marie-Jeanne, Rifqi, Maria, Castelltort, Arnaud

Publikováno v: 27èmes Rencontres Francophones sur la Logique Floue et ses Application
LFA: Logique Floue et ses Application
LFA: Logique Floue et ses Application, Nov 2018, Arras, France. pp.43-50

International audience; This paper proposes to exploit heterogeneous data, i.e. data described by both numerical and categorical features, so as to discover whether, based on information provided by the numerical attributes, some categorical attribut

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=od_______212::2c1610241bc964bed7ce6ab2f2c3e1c8
https://hal.archives-ouvertes.fr/hal-01917965

Compositional rule of inference as an analogical scheme

Autor: Bouchon-Meunier, Bernadette ^*, Mesiar, Radko, Marsala, Christophe, Rifqi, Maria

Publikováno v: In Fuzzy Sets and Systems 2003 138(1):53-65

EAST representation: fast discovery of discriminant temporal patterns from time series

Autor: Renard, Xavier, Rifqi, Maria, Fricout, Gabriel, Detyniecki, Marcin

Publikováno v: ECML/PKDD Workshop on Advanced Analytics and Learning on Temporal Data
ECML/PKDD Workshop on Advanced Analytics and Learning on Temporal Data, Sep 2016, Riva Del Garda, Italy

International audience; Mining discriminant temporal patterns is one problematic for the time series classification currently led by the shapelet. We expose this problematic under the angle of a standard feature-space classification task. This approa

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=dedup_wf_001::847728601df3098d2b80eb2d231eee0f
https://hal.sorbonne-universite.fr/hal-01350734

Contrasting data using gradual patterns

Autor: Laurent, Anne, Lesot, Marie-Jeanne, Rifqi, Maria

Publikováno v: Rencontres francophones sur la Logique Floue et ses Applications
LFA: Logique Floue et ses Applications
LFA: Logique Floue et ses Applications, Nov 2015, Poitiers, France

National audience; 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 em

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=dedup_wf_001::3a576030a8f1e1c8d08892d5f302be34
https://hal.archives-ouvertes.fr/hal-01276266/document

Random subspace oracle (RSO) ensemble to solve small sample-sized classification problems.

Autor: Ooi, Boon Pin, Abdul Rahim, Norasmadi, Zakaria, Ammar, Masnan, Maz Jamilah, Abdul Shukor, Shazmin Aniza, Batyrshin, Ildar, Cross, Valerie, Kreinovich, Vladik, Rifqi, Maria

Publikováno v: Journal of Intelligent & Fuzzy Systems; 2019, Vol. 36 Issue 4, p3225-3234, 10p