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A Robust Ensemble Approach to Learn From Positive and Unlabeled Data
  Using SVM Base Models
v1v2 (latest)

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
ArXiv (abs)PDFHTML

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
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
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
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
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
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
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
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
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
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
Hyperparameter Search in Machine Learning
Marc Claesen
B. De Moor
100
443
0
07 Feb 2015
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