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A Robust Ensemble Approach to Learn From Positive and Unlabeled Data Using SVM Base Models
13 February 2014
Marc Claesen
F. Smet
Johan A. K. Suykens
B. De Moor
NoLa
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Papers citing
"A Robust Ensemble Approach to Learn From Positive and Unlabeled Data Using SVM Base Models"
10 / 10 papers shown
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
23
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
31
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
89
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
88
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
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