Interpreting random forest classification models using a feature contribution method A Palczewska, J Palczewski, R Marchese Robinson, D Neagu Integration of reusable systems, 193-218, 2014 | 182 | 2014 |
Comparison of the predictive performance and interpretability of random forest and linear models on benchmark data sets RL Marchese Robinson, A Palczewska, J Palczewski, N Kidley Journal of chemical information and modeling 57 (8), 1773-1792, 2017 | 113 | 2017 |
Interpreting random forest models using a feature contribution method A Palczewska, J Palczewski, RM Robinson, D Neagu 2013 IEEE 14th international conference on Information Reuse & Integration …, 2013 | 92 | 2013 |
Data governance in predictive toxicology: A review X Fu, A Wojak, D Neagu, M Ridley, K Travis Journal of cheminformatics 3, 1-16, 2011 | 82 | 2011 |
Comparing the CORAL and Random Forest approaches for modelling the in vitro cytotoxicity of silica nanomaterials. A Cassano, RL Marchese Robinson, A Palczewska, T Puzyn, A Gajewicz, ... Altern Lab Anim 44 (6), 533-556, 2016 | 35 | 2016 |
Towards model governance in predictive toxicology A Palczewska, X Fu, P Trundle, L Yang, D Neagu, M Ridley, K Travis International Journal of Information Management 33 (3), 567-582, 2013 | 25 | 2013 |
A league-wide investigation into variability of rugby league match running from 322 Super League games N Dalton-Barron, A Palczewska, SJ McLaren, G Rennie, C Beggs, G Roe, ... Science and Medicine in Football 5 (3), 225-233, 2021 | 24 | 2021 |
A machine learning approach to short-term body weight prediction in a dietary intervention program O Babajide, T Hissam, P Anna, G Anatoliy, A Astrup, J Alfredo Martinez, ... Computational Science–ICCS 2020: 20th International Conference, Amsterdam …, 2020 | 23 | 2020 |
Sequential movement pattern-mining (SMP) in field-based team-sport: A framework for quantifying spatiotemporal data and improve training specificity? R White, A Palczewska, D Weaving, N Collins, B Jones Journal of Sports Sciences 40 (2), 164-174, 2022 | 8 | 2022 |
Using Pareto points for model identification in predictive toxicology A Palczewska, D Neagu, M Ridley Journal of Cheminformatics 5, 1-16, 2013 | 8 | 2013 |
Lccspm: l-length closed contiguous sequential patterns mining algorithm to find frequent athlete movement patterns from gps VE Adeyemo, A Palczewska, B Jones 2021 20th IEEE International Conference on Machine Learning and Applications …, 2021 | 7 | 2021 |
Development of an expected possession value model to analyse team attacking performances in rugby league T Sawczuk, A Palczewska, B Jones Plos one 16 (11), e0259536, 2021 | 7 | 2021 |
Application of unsupervised learning in weight-loss categorisation for weight management programs O Babajide, H Tawfik, A Palczewska, A Gorbenko, A Astrup, JA Martinez, ... 2019 10th International Conference on Dependable Systems, Services and …, 2019 | 6 | 2019 |
Moving beyond velocity derivatives; using global positioning system data to extract sequential movement patterns at different levels of rugby league match-play N Collins, R White, A Palczewska, D Weaving, N Dalton-Barron, B Jones European Journal of Sport Science 23 (2), 201-209, 2023 | 5 | 2023 |
Clustering of match running and performance indicators to assess between-and within-playing position similarity in professional rugby league N Dalton-Barron, A Palczewska, D Weaving, G Rennie, C Beggs, G Roe, ... Journal of Sports Sciences 40 (15), 1712-1721, 2022 | 4 | 2022 |
Identification of pattern mining algorithm for rugby league players positional groups separation based on movement patterns VE Adeyemo, A Palczewska, B Jones, D Weaving Plos one 19 (5), e0301608, 2024 | 3 | 2024 |
Markov decision processes with contextual nodes as a method of assessing attacking player performance in rugby league T Sawczuk, A Palczewska, B Jones Advances in Computational Intelligence Systems: Contributions Presented at …, 2022 | 3 | 2022 |
RobustSPAM for inference from noisy longitudinal data and preservation of privacy A Palczewska, J Palczewski, G Aivaliotis, L Kowalik 2017 16th IEEE international conference on machine learning and applications …, 2017 | 3 | 2017 |
Advances in Drug Toxicology U Gundert‑Remy, J Sachs, F Bévalot, IM McIntyre, A Palczewska, ... Advances in Drug Toxicology, 341, 2016 | 3 | 2016 |
In silico chemistry-based workflows to facilitate ADMET prediction for cosmetics-related substances AN Richarz, P Alov, SJ Enoch, S Kovarich, Y Lan, T Meinl, C Mellor, ... Toxicology Letters 2 (238), S170, 2015 | 3 | 2015 |