On the usefulness of the fit-on-test view on evaluating calibration of classifiers. - Kängsepp, Markus; Valk, Kaspar; Kull, Meelis (Mach. Learn., 2025)

Cost-sensitive classification with cost uncertainty: do we need surrogate losses? - Komisarenko, Viacheslav; Kull, Meelis (Mach. Learn., 2025)

Predicting the Activity of Unidentified Chemicals in Complementary Bioassays from the HRMS Data to Pinpoint Potential Endocrine Disruptors. - Rahu, Ida; Kull, Meelis; Kruve, Anneli (J. Chem. Inf. Model., 2024)

Cautious Calibration in Binary Classification. - Allikivi, Mari-Liis; Järve, Joonas; Kull, Meelis (2024)

Improving Calibration by Relating Focal Loss, Temperature Scaling, and Properness. - Komisarenko, Viacheslav; Kull, Meelis (2024)

Evaluation of Trajectory Distribution Predictions with Energy Score. - Shahroudi, Novin; Lepson, Mihkel; Kull, Meelis (2024)

Machine Learning and Knowledge Discovery in Databases. Research Track - European Conference, ECML PKDD 2024, Vilnius, Lithuania, September 9-13, 2024, Proceedings, Part I (Springer, 2024)

Machine Learning and Knowledge Discovery in Databases. Research Track - European Conference, ECML PKDD 2024, Vilnius, Lithuania, September 9-13, 2024, Proceedings, Part II (Springer, 2024)

Machine Learning and Knowledge Discovery in Databases. Research Track - European Conference, ECML PKDD 2024, Vilnius, Lithuania, September 9-13, 2024, Proceedings, Part III (Springer, 2024)

Machine Learning and Knowledge Discovery in Databases. Research Track - European Conference, ECML PKDD 2024, Vilnius, Lithuania, September 9-13, 2024, Proceedings, Part IV (Springer, 2024)

Machine Learning and Knowledge Discovery in Databases. Research Track - European Conference, ECML PKDD 2024, Vilnius, Lithuania, September 9-13, 2024, Proceedings, Part V (Springer, 2024)

Machine Learning and Knowledge Discovery in Databases. Research Track - European Conference, ECML PKDD 2024, Vilnius, Lithuania, September 9-13, 2024, Proceedings, Part VI (Springer, 2024)

Machine Learning and Knowledge Discovery in Databases. Research Track - European Conference, ECML PKDD 2024, Vilnius, Lithuania, September 9-13, 2024, Proceedings, Part VII (Springer, 2024)

Machine Learning and Knowledge Discovery in Databases. Research Track and Demo Track - European Conference, ECML PKDD 2024, Vilnius, Lithuania, September 9-13, 2024, Proceedings, Part VIII (Springer, 2024)

Cautious Calibration in Binary Classification. - Allikivi, Mari-Liis; Järve, Joonas; Kull, Meelis (CoRR, 2024)

Improving Calibration by Relating Focal Loss, Temperature Scaling, and Properness. - Komisarenko, Viacheslav; Kull, Meelis (CoRR, 2024)

Enhancing web traffic attacks identification through ensemble methods and feature selection. - Urda, Daniel; Martínez, Branly; Basurto, Nuño; Kull, Meelis; Arroyo, Ángel; Herrero, Álvaro (CoRR, 2024)

Classifier calibration: a survey on how to assess and improve predicted class probabilities. - Filho, Telmo de Menezes e Silva; Song, Hao; Perelló-Nieto, Miquel; Santos-Rodríguez, Raúl; Kull, Meelis; Flach, Peter A. (Mach. Learn., 2023)

Assuming Locally Equal Calibration Errors for Non-Parametric Multiclass Calibration. - Valk, Kaspar; Kull, Meelis (Trans. Mach. Learn. Res., 2023)

Generality-Training of a Classifier for Improved Calibration in Unseen Contexts. - Leelar, Bhawani Shankar; Kull, Meelis (2023)

Evaluating Classifiers' Performance to Detect Attacks in Website Traffic. - Urda, Daniel; Basurto, Nuño; Kull, Meelis; Herrero, Álvaro (2022)

Ethical and Fairness Implications of Model Multiplicity. - Sokol, Kacper; Kull, Meelis; Chan, Jeffrey; Salim, Flora Dilys (CoRR, 2022)

On the Usefulness of the Fit-on-the-Test View on Evaluating Calibration of Classifiers. - Kängsepp, Markus; Valk, Kaspar; Kull, Meelis (CoRR, 2022)

Calibrated Perception Uncertainty Across Objects and Regions in Bird's-Eye-View. - Kängsepp, Markus; Kull, Meelis (CoRR, 2022)

CRISP-DM Twenty Years Later: From Data Mining Processes to Data Science Trajectories. - Martínez-Plumed, Fernando; Ochando, Lidia Contreras; Ferri, Cèsar; Hernández-Orallo, José; Kull, Meelis; Lachiche, Nicolas; Ramírez-Quintana, María José; Flach, Peter A. (IEEE Trans. Knowl. Data Eng., 2021)

Instance-based Label Smoothing For Better Calibrated Classification Networks. - Maher, Mohamed; Kull, Meelis (2021)

Instance-based Label Smoothing For Better Calibrated Classification Networks. - Maher, Mohamed; Kull, Meelis (CoRR, 2021)

Shift Happens: Adjusting Classifiers. - Heiser, Theodore James Thibault; Allikivi, Mari-Liis; Kull, Meelis (CoRR, 2021)

Classifier Calibration: How to assess and improve predicted class probabilities: a survey. - Filho, Telmo de Menezes e Silva; Song, Hao; Perelló-Nieto, Miquel; Santos-Rodríguez, Raúl; Kull, Meelis; Flach, Peter A. (CoRR, 2021)

Correlated daily time series and forecasting in the M4 competition. - Ingel, Anti; Shahroudi, Novin; Kängsepp, Markus; Tättar, Andre; Komisarenko, Viacheslav; Kull, Meelis (CoRR, 2020)

Distribution calibration for regression. - Song, Hao; Diethe, Tom; Kull, Meelis; Flach, Peter A. (2019)

Beyond temperature scaling: Obtaining well-calibrated multi-class probabilities with Dirichlet calibration. - Kull, Meelis; Perelló-Nieto, Miquel; Kängsepp, Markus; Filho, Telmo de Menezes e Silva; Song, Hao; Flach, Peter A. (2019)

Shift Happens: Adjusting Classifiers. - Heiser, Theodore James Thibault; Allikivi, Mari-Liis; Kull, Meelis (2019)

Non-parametric Bayesian Isotonic Calibration: Fighting Over-Confidence in Binary Classification. - Allikivi, Mari-Liis; Kull, Meelis (2019)

Distribution Calibration for Regression. - Song, Hao; Diethe, Tom; Kull, Meelis; Flach, Peter A. (CoRR, 2019)

HyperStream: a Workflow Engine for Streaming Data. - Diethe, Tom; Kull, Meelis; Twomey, Niall; Sokol, Kacper; Song, Hao; Perelló-Nieto, Miquel; Tonkin, Emma; Flach, Peter A. (CoRR, 2019)

Beyond temperature scaling: Obtaining well-calibrated multiclass probabilities with Dirichlet calibration. - Kull, Meelis; Perelló-Nieto, Miquel; Kängsepp, Markus; Filho, Telmo de Menezes e Silva; Song, Hao; Flach, Peter A. (CoRR, 2019)

Releasing eHealth Analytics into the Wild: Lessons Learnt from the SPHERE Project. - Diethe, Tom; Holmes, Mike; Kull, Meelis; Perelló-Nieto, Miquel; Sokol, Kacper; Song, Hao; Tonkin, Emma; Twomey, Niall; Flach, Peter A. (2018)

Non-Parametric Calibration of Probabilistic Regression. - Song, Hao; Kull, Meelis; Flach, Peter A. (CoRR, 2018)

Beta calibration: a well-founded and easily implemented improvement on logistic calibration for binary classifiers. - Kull, Meelis; Filho, Telmo de Menezes e Silva; Flach, Peter A. (2017)

Probabilistic Sensor Fusion for Ambient Assisted Living. - Diethe, Tom; Twomey, Niall; Kull, Meelis; Flach, Peter A.; Craddock, Ian (CoRR, 2017)

CASP-DM: Context Aware Standard Process for Data Mining. - Martínez-Plumed, Fernando; Ochando, Lidia Contreras; Ferri, César; Flach, Peter A.; Hernández-Orallo, José; Kull, Meelis; Lachiche, Nicolas; Ramírez-Quintana, María José (CoRR, 2017)

Reframing in context: A systematic approach for model reuse in machine learning. - Hernández-Orallo, José; Usó, Adolfo Martínez; Prudêncio, Ricardo B. C.; Kull, Meelis; Flach, Peter A.; Ahmed, Chowdhury Farhan; Lachiche, Nicolas (AI Commun., 2016)

Cost-sensitive boosting algorithms: Do we really need them? - Nikolaou, Nikolaos; Edakunni, Narayanan Unny; Kull, Meelis; Flach, Peter A.; Brown, Gavin (Mach. Learn., 2016)

Declaratively Capturing Local Label Correlations with Multi-Label Trees. - Al-Otaibi, Reem; Kull, Meelis; Flach, Peter A. (2016)

Background Check: A General Technique to Build More Reliable and Versatile Classifiers. - Perelló-Nieto, Miquel; Filho, Telmo de Menezes e Silva; Kull, Meelis; Flach, Peter A. (2016)

Subgroup Discovery with Proper Scoring Rules. - Song, Hao; Kull, Meelis; Flach, Peter A.; Kalogridis, Georgios (2016)

The SPHERE Challenge: Activity Recognition with Multimodal Sensor Data. - Twomey, Niall; Diethe, Tom; Kull, Meelis; Song, Hao; Camplani, Massimo; Hannuna, Sion L.; Fafoutis, Xenofon; Zhu, Ni; Woznowski, Pete; Flach, Peter A.; Craddock, Ian (CoRR, 2016)

Reframing in Frequent Pattern Mining. - Ahmed, Chowdhury Farhan; Samiullah, Md.; Lachiche, Nicolas; Kull, Meelis; Flach, Peter A. (2015)

Precision-Recall-Gain Curves: PR Analysis Done Right. - Flach, Peter A.; Kull, Meelis (2015)

Novel Decompositions of Proper Scoring Rules for Classification: Score Adjustment as Precursor to Calibration. - Kull, Meelis; Flach, Peter A. (2015)

Versatile Decision Trees for Learning Over Multiple Contexts. - Al-Otaibi, Reem; Prudêncio, Ricardo B. C.; Kull, Meelis; Flach, Peter A. (2015)

Model Reuse with Bike rental Station data (Preamble). - Kull, Meelis; Lachiche, Nicolas; Usó, Adolfo Martínez (2015)

Proceedings of the ECML/PKDD 2015 Discovery Challenges co-located with European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML-PKDD 2015), Porto, Portugal, September 7-11, 2015. (CEUR-WS.org, 2015)

LaCova: A Tree-Based Multi-label Classifier Using Label Covariance as Splitting Criterion. - Al-Otaibi, Reem; Kull, Meelis; Flach, Peter A. (2014)

Reliability Maps: A Tool to Enhance Probability Estimates and Improve Classification Accuracy. - Kull, Meelis; Flach, Peter A. (2014)

Rate-Oriented Point-Wise Confidence Bounds for ROC Curves. - Millard, Louise A. C.; Kull, Meelis; Flach, Peter A. (2014)

An Evolutionary Model of DNA Substring Distribution. - Kull, Meelis; Tretyakov, Konstantin; Vilo, Jaak (2010)

VisHiC - hierarchical functional enrichment analysis of microarray data. - Krushevskaya, Darya; Peterson, Hedi; Reimand, Jüri; Kull, Meelis; Vilo, Jaak (Nucleic Acids Res., 2009)

Fast approximate hierarchical clustering using similarity heuristics. - Kull, Meelis; Vilo, Jaak (BioData Min., 2008)

g: Profiler - a web-based toolset for functional profiling of gene lists from large-scale experiments. - Reimand, Jüri; Kull, Meelis; Peterson, Hedi; Hansen, Jaanus; Vilo, Jaak (Nucleic Acids Res., 2007)

Expression Profiler: next generation - an online platform for analysis of microarray data. - Kapushesky, Misha; Kemmeren, Patrick; Culhane, Aedín C.; Durinck, Steffen; Ihmels, Jan; Körner, Christine; Kull, Meelis; Torrente, Aurora; Sarkans, Ugis; Vilo, Jaak; Brazma, Alvis (Nucleic Acids Res., 2004)