A dual algorithmic approach to deal with multiclass imbalanced classification problems

Author:

Sridhar S.ORCID,Anusuya S.

Publisher

Elsevier BV

Reference25 articles.

1. Abdellatif, S., Ben Hassine, M.A., Ben Yahia, S., Bouzeghoub, A. (2018). ARCID: a new approach to deal with imbalanced datasets classification. In: Tjoa, A., Bellatreche, L., Biffl, S., van Leeuwen, J., Wiedermann, J. SOFSEM 2018. Lecture Notes in Computer Science, vol 10706. Edizioni dellaNormale, Cham.

2. Sketching, embedding and dimensionality reduction in information theoretic spaces;Abdullah;Artif. Intell. Statis,2016

3. An iterative method for multi–class cost–sensitive learning;Abe,2004

4. Cost-sensitive decision tree ensembles for effective imbalanced classification;Krawczyk;Appl. Soft. Comput,2014

5. MWMOTE–majority weighted minority oversampling technique for imbalanced data set learning;Barua,2014

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