Meelis Kull
Title
Cited by
Cited by
Year
g: Profiler—a web-based toolset for functional profiling of gene lists from large-scale experiments
J Reimand, M Kull, H Peterson, J Hansen, J Vilo
Nucleic acids research 35 (suppl_2), W193-W200, 2007
9552007
Precision-Recall-Gain Curves: PR Analysis Done Right.
PA Flach, M Kull
NIPS 15, 2015
2052015
Mining for coexpression across hundreds of datasets using novel rank aggregation and visualization methods
P Adler, R Kolde, M Kull, A Tkachenko, H Peterson, J Reimand, J Vilo
Genome biology 10 (12), 1-11, 2009
1602009
Expression Profiler: next generation—an online platform for analysis of microarray data
M Kapushesky, P Kemmeren, AC Culhane, S Durinck, J Ihmels, C Körner, ...
Nucleic acids research 32 (suppl_2), W465-W470, 2004
1522004
ASTD: the alternative splicing and transcript diversity database
G Koscielny, V Le Texier, C Gopalakrishnan, V Kumanduri, JJ Riethoven, ...
Genomics 93 (3), 213-220, 2009
1242009
Beyond temperature scaling: Obtaining well-calibrated multiclass probabilities with Dirichlet calibration
M Kull, M Perello-Nieto, M Kängsepp, H Song, P Flach
arXiv preprint arXiv:1910.12656, 2019
992019
Beta calibration: a well-founded and easily implemented improvement on logistic calibration for binary classifiers
M Kull, T Silva Filho, P Flach
Artificial Intelligence and Statistics, 623-631, 2017
782017
CRISP-DM twenty years later: From data mining processes to data science trajectories
F Martínez-Plumed, L Contreras-Ochando, C Ferri, JH Orallo, M Kull, ...
IEEE Transactions on Knowledge and Data Engineering, 2019
692019
The SPHERE challenge: Activity recognition with multimodal sensor data
N Twomey, T Diethe, M Kull, H Song, M Camplani, S Hannuna, X Fafoutis, ...
arXiv preprint arXiv:1603.00797, 2016
642016
Cost-sensitive boosting algorithms: Do we really need them?
N Nikolaou, N Edakunni, M Kull, P Flach, G Brown
Machine Learning 104 (2), 359-384, 2016
542016
Beyond sigmoids: How to obtain well-calibrated probabilities from binary classifiers with beta calibration
M Kull, TM Silva Filho, P Flach
Electronic Journal of Statistics 11 (2), 5052-5080, 2017
472017
Distribution calibration for regression
H Song, T Diethe, M Kull, P Flach
Proceedings of the 36th International Conference on Machine Learning (ICML …, 2019
402019
Comprehensive transcriptome analysis of mouse embryonic stem cell adipogenesis unravels new processes of adipocyte development
N Billon, R Kolde, J Reimand, MC Monteiro, M Kull, H Peterson, ...
Genome biology 11 (8), 1-16, 2010
382010
Novel decompositions of proper scoring rules for classification: Score adjustment as precursor to calibration
M Kull, P Flach
Joint European Conference on Machine Learning and Knowledge Discovery in …, 2015
312015
Fast approximate hierarchical clustering using similarity heuristics
M Kull, J Vilo
BioData mining 1, 9, 2008
312008
Patterns of dataset shift
M Kull, P Flach
First International Workshop on Learning over Multiple Contexts (LMCE) at …, 2014
282014
Reliability maps: a tool to enhance probability estimates and improve classification accuracy
M Kull, PA Flach
Joint European Conference on Machine Learning and Knowledge Discovery in …, 2014
182014
Releasing ehealth analytics into the wild: Lessons learnt from the sphere project
T Diethe, M Holmes, M Kull, M Perello Nieto, K Sokol, H Song, E Tonkin, ...
Proceedings of the 24th ACM SIGKDD International Conference on Knowledge …, 2018
152018
Probabilistic sensor fusion for ambient assisted living
T Diethe, N Twomey, M Kull, P Flach, I Craddock
arXiv preprint arXiv:1702.01209, 2017
142017
Background Check: A general technique to build more reliable and versatile classifiers
M Perello-Nieto, ES Telmo De Menezes Filho, M Kull, P Flach
2016 IEEE 16th International Conference on Data Mining (ICDM), 1143-1148, 2016
122016
The system can't perform the operation now. Try again later.
Articles 1–20