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Oversampling for Imbalanced Learning Based on K-Means and SMOTE

Oversampling for Imbalanced Learning Based on K-Means and SMOTE

2 November 2017
F. Last
G. Douzas
F. Bação
ArXivPDFHTML

Papers citing "Oversampling for Imbalanced Learning Based on K-Means and SMOTE"

4 / 4 papers shown
Title
Provable Imbalanced Point Clustering
Provable Imbalanced Point Clustering
David Denisov
Dan Feldman
Shlomi Dolev
Michael Segal
102
0
0
13 Mar 2025
Reproducible Machine Learning-based Voice Pathology Detection: Introducing the Pitch Difference Feature
Reproducible Machine Learning-based Voice Pathology Detection: Introducing the Pitch Difference Feature
Jan Vrba
Jakub Steinbach
Tomáš Jirsa
Laura Verde
Roberta De Fazio
...
Lukáš Hájek
Zuzana Sedláková
Jan Mareš
Jan Mareš
Noriyasu Homma
42
0
0
14 Oct 2024
Imbalanced-learn: A Python Toolbox to Tackle the Curse of Imbalanced
  Datasets in Machine Learning
Imbalanced-learn: A Python Toolbox to Tackle the Curse of Imbalanced Datasets in Machine Learning
G. Lemaître
Fernando Nogueira
Christos K. Aridas
53
2,052
0
21 Sep 2016
SMOTE: Synthetic Minority Over-sampling Technique
SMOTE: Synthetic Minority Over-sampling Technique
Nitesh Chawla
Kevin W. Bowyer
Lawrence Hall
W. Kegelmeyer
AI4TS
267
25,443
0
09 Jun 2011
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