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).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
569580
Ilmunud
3.1. Artiklid/peatükid lisas loetletud kirjastuste välja antud kogumikes (kaasa arvatud Thomson Reuters Book Citation Index, Thomson Reuters Conference Proceedings Citation Index, Scopus refereeritud kogumikud)

Viited terviktekstile

doi.org/10.1007/978-3-319-73117-9_40

Seotud asutused

University of Tunis El Manar, Tunis, Tunisia

Lisainfo

associative classification; imbalanced datasets; machine learning; data mining
Scopus