Meelis Kull

Publication Activity (10 Years)

Years Active: 2004-2024
Publications (10 Years): 37

Top Topics

Data Mining Processes

Class Probabilities

Top Venues

Publications

Ida Rahu, Meelis Kull, Anneli Kruve
Predicting the Activity of Unidentified Chemicals in Complementary Bioassays from the HRMS Data to Pinpoint Potential Endocrine Disruptors. J. Chem. Inf. Model. 64 (8) (2024)
Kaspar Valk, Meelis Kull
Assuming Locally Equal Calibration Errors for Non-Parametric Multiclass Calibration. Trans. Mach. Learn. Res. 2023 (2023)
Bhawani Shankar Leelar, Meelis Kull
Generality-Training of a Classifier for Improved Calibration in Unseen Contexts. ECML/PKDD (5) (2023)
Telmo de Menezes e Silva Filho, Hao Song, Miquel Perelló-Nieto, Raúl Santos-Rodríguez, Meelis Kull, Peter A. Flach
Classifier calibration: a survey on how to assess and improve predicted class probabilities. Mach. Learn. 112 (9) (2023)
Markus Kängsepp, Kaspar Valk, Meelis Kull
On the Usefulness of the Fit-on-the-Test View on Evaluating Calibration of Classifiers. CoRR (2022)
Daniel Urda, Nuño Basurto, Meelis Kull, Álvaro Herrero
Evaluating Classifiers' Performance to Detect Attacks in Website Traffic. CISIS-ICEUTE (2022)
Markus Kängsepp, Meelis Kull
Calibrated Perception Uncertainty Across Objects and Regions in Bird's-Eye-View. CoRR (2022)
Kacper Sokol, Meelis Kull, Jeffrey Chan, Flora Dilys Salim
Ethical and Fairness Implications of Model Multiplicity. CoRR (2022)
Telmo de Menezes e Silva Filho, Hao Song, Miquel Perelló-Nieto, Raúl Santos-Rodríguez, Meelis Kull, Peter A. Flach
Classifier Calibration: How to assess and improve predicted class probabilities: a survey. CoRR (2021)
Mohamed Maher, Meelis Kull
Instance-based Label Smoothing For Better Calibrated Classification Networks. CoRR (2021)
Theodore James Thibault Heiser, Mari-Liis Allikivi, Meelis Kull
Shift Happens: Adjusting Classifiers. CoRR (2021)
Fernando Martínez-Plumed, Lidia Contreras Ochando, Cèsar Ferri, José Hernández-Orallo, Meelis Kull, Nicolas Lachiche, María José Ramírez-Quintana, Peter A. Flach
CRISP-DM Twenty Years Later: From Data Mining Processes to Data Science Trajectories. IEEE Trans. Knowl. Data Eng. 33 (8) (2021)
Mohamed Maher, Meelis Kull
Instance-based Label Smoothing For Better Calibrated Classification Networks. ICMLA (2021)
Anti Ingel, Novin Shahroudi, Markus Kängsepp, Andre Tättar, Viacheslav Komisarenko, Meelis Kull
Correlated daily time series and forecasting in the M4 competition. CoRR (2020)
Hao Song, Tom Diethe, Meelis Kull, Peter A. Flach
Distribution Calibration for Regression. CoRR (2019)
Mari-Liis Allikivi, Meelis Kull
Non-parametric Bayesian Isotonic Calibration: Fighting Over-Confidence in Binary Classification. ECML/PKDD (2) (2019)
Meelis Kull, Miquel Perelló-Nieto, Markus Kängsepp, Telmo de Menezes e Silva Filho, Hao Song, Peter A. Flach
Beyond temperature scaling: Obtaining well-calibrated multiclass probabilities with Dirichlet calibration. CoRR (2019)
Theodore James Thibault Heiser, Mari-Liis Allikivi, Meelis Kull
Shift Happens: Adjusting Classifiers. ECML/PKDD (2) (2019)
Tom Diethe, Meelis Kull, Niall Twomey, Kacper Sokol, Hao Song, Miquel Perelló-Nieto, Emma Tonkin, Peter A. Flach
HyperStream: a Workflow Engine for Streaming Data. CoRR (2019)
Meelis Kull, Miquel Perelló-Nieto, Markus Kängsepp, Telmo de Menezes e Silva Filho, Hao Song, Peter A. Flach
Beyond temperature scaling: Obtaining well-calibrated multi-class probabilities with Dirichlet calibration. NeurIPS (2019)
Hao Song, Tom Diethe, Meelis Kull, Peter A. Flach
Distribution calibration for regression. ICML (2019)
Tom Diethe, Mike Holmes, Meelis Kull, Miquel Perelló-Nieto, Kacper Sokol, Hao Song, Emma Tonkin, Niall Twomey, Peter A. Flach
Releasing eHealth Analytics into the Wild: Lessons Learnt from the SPHERE Project. KDD (2018)
Hao Song, Meelis Kull, Peter A. Flach
Non-Parametric Calibration of Probabilistic Regression. CoRR (2018)
Fernando Martínez-Plumed, Lidia Contreras Ochando, César Ferri, Peter A. Flach, José Hernández-Orallo, Meelis Kull, Nicolas Lachiche, María José Ramírez-Quintana
CASP-DM: Context Aware Standard Process for Data Mining. CoRR (2017)
Tom Diethe, Niall Twomey, Meelis Kull, Peter A. Flach, Ian Craddock
Probabilistic Sensor Fusion for Ambient Assisted Living. CoRR (2017)
Meelis Kull, Telmo de Menezes e Silva Filho, Peter A. Flach
Beta calibration: a well-founded and easily implemented improvement on logistic calibration for binary classifiers. AISTATS (2017)
José Hernández-Orallo, Adolfo Martínez Usó, Ricardo B. C. Prudêncio, Meelis Kull, Peter A. Flach, Chowdhury Farhan Ahmed, Nicolas Lachiche
Reframing in context: A systematic approach for model reuse in machine learning. AI Commun. 29 (5) (2016)
Niall Twomey, Tom Diethe, Meelis Kull, Hao Song, Massimo Camplani, Sion L. Hannuna, Xenofon Fafoutis, Ni Zhu, Pete Woznowski, Peter A. Flach, Ian Craddock
The SPHERE Challenge: Activity Recognition with Multimodal Sensor Data. CoRR (2016)
Reem Al-Otaibi, Meelis Kull, Peter A. Flach
Declaratively Capturing Local Label Correlations with Multi-Label Trees. ECAI (2016)
Hao Song, Meelis Kull, Peter A. Flach, Georgios Kalogridis
Subgroup Discovery with Proper Scoring Rules. ECML/PKDD (2) (2016)
Nikolaos Nikolaou, Narayanan Unny Edakunni, Meelis Kull, Peter A. Flach, Gavin Brown
Cost-sensitive boosting algorithms: Do we really need them? Mach. Learn. 104 (2-3) (2016)
Miquel Perelló-Nieto, Telmo de Menezes e Silva Filho, Meelis Kull, Peter A. Flach
Background Check: A General Technique to Build More Reliable and Versatile Classifiers. ICDM (2016)
Meelis Kull, Nicolas Lachiche, Adolfo Martínez Usó
Model Reuse with Bike rental Station data (Preamble). DC@PKDD/ECML (2015)
Reem Al-Otaibi, Ricardo B. C. Prudêncio, Meelis Kull, Peter A. Flach
Versatile Decision Trees for Learning Over Multiple Contexts. ECML/PKDD (1) (2015)
Peter A. Flach, Meelis Kull
Precision-Recall-Gain Curves: PR Analysis Done Right. NIPS (2015)
Chowdhury Farhan Ahmed, Md. Samiullah, Nicolas Lachiche, Meelis Kull, Peter A. Flach
Reframing in Frequent Pattern Mining. ICTAI (2015)
Meelis Kull, Peter A. Flach
Novel Decompositions of Proper Scoring Rules for Classification: Score Adjustment as Precursor to Calibration. ECML/PKDD (1) (2015)
Meelis Kull, Peter A. Flach
Reliability Maps: A Tool to Enhance Probability Estimates and Improve Classification Accuracy. ECML/PKDD (2) (2014)
Reem Al-Otaibi, Meelis Kull, Peter A. Flach
LaCova: A Tree-Based Multi-label Classifier Using Label Covariance as Splitting Criterion. ICMLA (2014)
Louise A. C. Millard, Meelis Kull, Peter A. Flach
Rate-Oriented Point-Wise Confidence Bounds for ROC Curves. ECML/PKDD (2) (2014)
Meelis Kull, Konstantin Tretyakov, Jaak Vilo
An Evolutionary Model of DNA Substring Distribution. Algorithms and Applications (2010)
Darya Krushevskaya, Hedi Peterson, Jüri Reimand, Meelis Kull, Jaak Vilo
VisHiC - hierarchical functional enrichment analysis of microarray data. Nucleic Acids Res. 37 (Web-Server-Issue) (2009)
Meelis Kull, Jaak Vilo
Fast approximate hierarchical clustering using similarity heuristics. BioData Min. 1 (2008)
Jüri Reimand, Meelis Kull, Hedi Peterson, Jaanus Hansen, Jaak Vilo
g: Profiler - a web-based toolset for functional profiling of gene lists from large-scale experiments. Nucleic Acids Res. 35 (Web-Server-Issue) (2007)
Misha Kapushesky, Patrick Kemmeren, Aedín C. Culhane, Steffen Durinck, Jan Ihmels, Christine Körner, Meelis Kull, Aurora Torrente, Ugis Sarkans, Jaak Vilo, Alvis Brazma
Expression Profiler: next generation - an online platform for analysis of microarray data. Nucleic Acids Res. 32 (Web-Server-Issue) (2004)