A Robust Ensemble Approach to Learn From Positive and Unlabeled Data
Using SVM Base Models

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A Robust Ensemble Approach to Learn From Positive and Unlabeled Data Using SVM Base Models

13 February 2014

Johan A. K. Suykens

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Papers citing "A Robust Ensemble Approach to Learn From Positive and Unlabeled Data Using SVM Base Models"

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Title
An Effective Flow-based Method for Positive-Unlabeled Learning: 2-HNC Dorit Hochbaum Torpong Nitayanont 96 0 0 13 May 2025
An Effective Approach for Multi-label Classification with Missing Labels Xin Zhang R. Abdelfattah Yuqi Song Xiang Wang 50 4 0 24 Oct 2022
Fairness-aware Model-agnostic Positive and Unlabeled Learning Ziwei Wu Jingrui He FaML 114 12 0 19 Jun 2022
Evaluating the Predictive Performance of Positive-Unlabelled Classifiers: a brief critical review and practical recommendations for improvement Jack D. Saunders Alex A. Freitas 25 3 0 06 Jun 2022
NIAPU: network-informed adaptive positive-unlabeled learning for disease gene identification P. Stolfi Andrea Mastropietro G. Pasculli Paolo Tieri D. Vergni MedIm 33 7 0 13 Aug 2021
Learning from positive and unlabeled data: a survey Jessa Bekker Jesse Davis 89 569 0 12 Nov 2018
Beyond the Selected Completely At Random Assumption for Learning from Positive and Unlabeled Data Jessa Bekker Pieter Robberechts Jesse Davis 91 84 0 10 Sep 2018
Learning with Confident Examples: Rank Pruning for Robust Classification with Noisy Labels Curtis G. Northcutt Tailin Wu Isaac L. Chuang NoLa 90 160 0 04 May 2017
Assessing binary classifiers using only positive and unlabeled data Marc Claesen Jesse Davis F. Smet B. De Moor 71 20 0 26 Apr 2015
Hyperparameter Search in Machine Learning Marc Claesen B. De Moor 100 443 0 07 Feb 2015