关注
Willem Waegeman
Willem Waegeman
在 ugent.be 的电子邮件经过验证 - 首页
标题
引用次数
引用次数
年份
Aleatoric and epistemic uncertainty in machine learning: An introduction to concepts and methods
E Hüllermeier, W Waegeman
Machine Learning 110 (3), 457-506, 2021
13142021
A community effort to assess and improve drug sensitivity prediction algorithms
JC Costello, LM Heiser, E Georgii, M Gönen, MP Menden, NJ Wang, ...
Nature biotechnology 32 (12), 1202-1212, 2014
7732014
On label dependence and loss minimization in multi-label classification
K Dembczyński, W Waegeman, W Cheng, E Hüllermeier
Machine Learning 88 (1-2), 5-45, 2012
4842012
Absolute quantification of microbial taxon abundances
R Props, FM Kerckhof, P Rubbens, J De Vrieze, E Hernandez Sanabria, ...
The ISME journal 11 (2), 584-587, 2017
3342017
Bacterial species identification from MALDI-TOF mass spectra through data analysis and machine learning
K De Bruyne, B Slabbinck, W Waegeman, P Vauterin, B De Baets, ...
Systematic and applied microbiology 34 (1), 20-29, 2011
2632011
An experimental comparison of cross-validation techniques for estimating the area under the ROC curve
A Airola, T Pahikkala, W Waegeman, B De Baets, T Salakoski
Computational Statistics & Data Analysis 55 (4), 1828-1844, 2011
1952011
An exact algorithm for F-measure maximization
K Dembczynski, W Waegeman, W Cheng, E Hüllermeier
Advances in neural information processing systems 24, 2011
1532011
Effects of chlorhexidine gluconate oral care on hospital mortality: a hospital-wide, observational cohort study
M Deschepper, W Waegeman, K Eeckloo, D Vogelaers, S Blot
Intensive care medicine 44, 1017-1026, 2018
1512018
ROC analysis in ordinal regression learning
W Waegeman, B De Baets, L Boullart
Pattern Recognition Letters 29 (1), 1-9, 2008
1502008
Habitat prediction and knowledge extraction for spawning European grayling (Thymallus thymallus L.) using a broad range of species distribution models
S Fukuda, B De Baets, W Waegeman, J Verwaeren, AM Mouton
Environmental modelling & software 47, 1-6, 2013
1472013
Vegetation anomalies caused by antecedent precipitation in most of the world
C Papagiannopoulou, DG Miralles, WA Dorigo, NEC Verhoest, ...
Environmental Research Letters 12 (7), 074016, 2017
1432017
A non-linear Granger-causality framework to investigate climate–vegetation dynamics
C Papagiannopoulou, DG Miralles, S Decubber, M Demuzere, ...
Geoscientific Model Development 10 (5), 1945-1960, 2017
1352017
Optimizing the F-measure in multi-label classification: Plug-in rule approach versus structured loss minimization
K Dembczynski, A Jachnik, W Kotlowski, W Waegeman, E Hüllermeier
International conference on machine learning, 1130-1138, 2013
1322013
Multi-target prediction: a unifying view on problems and methods
W Waegeman, K Dembczyński, E Hüllermeier
Data Mining and Knowledge Discovery 33, 293-324, 2019
1052019
A comparison of AUC estimators in small-sample studies
A Airola, T Pahikkala, W Waegeman, B De Baets, T Salakoski
Machine learning in systems biology, 3-13, 2009
962009
Exploration and prediction of interactions between methanotrophs and heterotrophs
M Stock, S Hoefman, FM Kerckhof, N Boon, P De Vos, B De Baets, ...
Research in microbiology 164 (10), 1045-1054, 2013
822013
An analysis of chaining in multi-label classification
K Dembczyński, W Waegeman, E Hüllermeier
ECAI 2012, 294-299, 2012
822012
On the bayes-optimality of f-measure maximizers
W Waegeman, K Dembczyński, A Jachnik, W Cheng, E Hüllermeier
Journal of Machine Learning Research 15, 3333-3388, 2014
812014
Connection between primary Fusarium inoculum on gramineous weeds, crop residues and soil samples and the final population on wheat ears in Flanders, Belgium
S Landschoot, K Audenaert, W Waegeman, B Pycke, B Bekaert, ...
Crop Protection 30 (10), 1297-1305, 2011
752011
Regret analysis for performance metrics in multi-label classification: the case of hamming and subset zero-one loss
K Dembczyński, W Waegeman, W Cheng, E Hüllermeier
Machine Learning and Knowledge Discovery in Databases: European Conference …, 2010
732010
系统目前无法执行此操作,请稍后再试。
文章 1–20