| DNA-based predictive models for the presence of freckles M Kukla-Bartoszek, E Pośpiech, A Woźniak, M Boroń, J Karłowska-Pik, ... Forensic Science International: Genetics 42, 252-259, 2019 | 38 | 2019 |
| Cost-sensitive classifier chains: Selecting low-cost features in multi-label classification P Teisseyre, D Zufferey, M Słomka Pattern Recognition 86, 290-319, 2019 | 33 | 2019 |
| Using random subspace method for prediction and variable importance assessment in linear regression J Mielniczuk, P Teisseyre Computational Statistics & Data Analysis 71, 725-742, 2014 | 33 | 2014 |
| Stopping rules for mutual information-based feature selection J Mielniczuk, P Teisseyre Neurocomputing 358, 255-274, 2019 | 30 | 2019 |
| CCnet: Joint multi-label classification and feature selection using classifier chains and elastic net regularization P Teisseyre Neurocomputing 235, 98-111, 2017 | 27 | 2017 |
| Different strategies of fitting logistic regression for positive and unlabelled data P Teisseyre, J Mielniczuk, M Łazęcka International Conference on Computational Science, 3-17, 2020 | 26 | 2020 |
| Diversity of editors and teams versus quality of cooperative work: experiments on Wikipedia M Sydow, K Baraniak, P Teisseyre Journal of Intelligent Information Systems 48, 601-632, 2017 | 22 | 2017 |
| Classifier chains for positive unlabelled multi-label learning P Teisseyre Knowledge-Based Systems 213, 106709, 2021 | 20 | 2021 |
| Estimating the class prior for positive and unlabelled data via logistic regression M Łazęcka, J Mielniczuk, P Teisseyre Advances in Data Analysis and Classification 15 (4), 1039-1068, 2021 | 16 | 2021 |
| Unveiling new interdependencies between significant DNA methylation sites, gene expression profiles and glioma patients survival MJ Dabrowski, M Draminski, K Diamanti, K Stepniak, MA Mozolewska, ... Scientific reports 8 (1), 4390, 2018 | 16 | 2018 |
| Feature ranking for multi-label classification using Markov networks P Teisseyre Neurocomputing 205, 439-454, 2016 | 16 | 2016 |
| How to gain on power: novel conditional independence tests based on short expansion of conditional mutual information M Kubkowski, J Mielniczuk, P Teisseyre Journal of Machine Learning Research 22 (62), 1-57, 2021 | 13 | 2021 |
| Controlling costs in feature selection: information theoretic approach P Teisseyre, T Klonecki Computational Science–ICCS 2021: 21st International Conference, Krakow …, 2021 | 12 | 2021 |
| Predicting physical appearance from DNA data—Towards genomic solutions E Pośpiech, P Teisseyre, J Mielniczuk, W Branicki Genes 13 (1), 121, 2022 | 11 | 2022 |
| A deeper look at two concepts of measuring gene–gene interactions: logistic regression and interaction information revisited J Mielniczuk, P Teisseyre Genetic Epidemiology 42 (2), 187-200, 2018 | 11 | 2018 |
| Random Subspace Method for high-dimensional regression with the R package regRSM P Teisseyre, RA Kłopotek, J Mielniczuk Computational Statistics 31, 943-972, 2016 | 8 | 2016 |
| Analysing utterances in polish parliament to predict speaker’s background P Przybyła, P Teisseyre Journal of quantitative linguistics 21 (4), 350-376, 2014 | 8 | 2014 |
| Searching for improvements in predicting human eye colour from DNA M Kukla-Bartoszek, P Teisseyre, E Pośpiech, J Karłowska-Pik, P Zieliński, ... International Journal of Legal Medicine 135 (6), 2175-2187, 2021 | 7 | 2021 |
| Information-theoretic feature selection using high-order interactions M Pawluk, P Teisseyre, J Mielniczuk Machine Learning, Optimization, and Data Science: 4th International …, 2019 | 7 | 2019 |
| What do your look-alikes say about you? Exploiting strong and weak similarities for author profiling P Przybyła, P Teisseyre CEUR Workshop Proceedings 1391, 2015 | 7 | 2015 |
Jan MielniczukPolish Academy of Sciences, Warsaw University of TechnologyZweryfikowany adres z ipipan.waw.pl
