ARCID: A new approach to deal with imbalanced datasets classification
Abdellatif, Safa; Ben Hassine, Mohamed Ali; Ben Yahia, Sadok; Bouzeghoub, Amel; (2018). ARCID: A new approach to deal with imbalanced datasets classification. SOFSEM 2018 : Theory and Practiceof Computer Science, 44th International Conference on Current Trendsin Theory and Practice of Computer Science : Krems, Austria, January 29–February 2, 2018, Proceedings. Ed. Tjoa, A. Min; Bellatreche, Ladjel; Biffl, Stefan; van Leeuwen, Jan; Wiedermann, Jiří. Cham: Springer, 569−580. (Lecture Notes in Computer Science; 10706). DOI: 10.1007/978-3-319-73117-9_40.
publitseeritud konverentsiettekanne
Abdellatif, Safa; Ben Hassine, Mohamed Ali; Ben Yahia, Sadok; Bouzeghoub, Amel;
- Inglise
SOFSEM 2018 : Theory and Practiceof Computer Science, 44th International Conference on Current Trendsin Theory and Practice of Computer Science : Krems, Austria, January 29–February 2, 2018, Proceedings
Tjoa, A. Min; Bellatreche, Ladjel; Biffl, Stefan; van Leeuwen, Jan; Wiedermann, Jiří
Cham
0302-9743
978-3-319-73116-2
Lecture Notes in Computer Science
10706
2018
569–580
Ilmunud
3.1. Artiklid/peatükid lisas loetletud kirjastuste välja antud kogumikes (kaasa arvatud Web of Science Book Citation Index, Web of Science Conference Proceedings Citation Index, Scopus refereeritud kogumikud)
Ei
Viited terviktekstile
Seotud asutused
University of Tunis El Manar, Tunis, Tunisia
Lisainfo
associative classification; imbalanced datasets; machine learning; data mining
WoS CPCI; Scopus