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Anna Palczewska
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2020 – today
- 2023
- [c15]Balbir Singh
, Anatoliy Gorbenko
, Anna Palczewska
, Hissam Tawfik
:
Application of Machine Learning Techniques to Predict Teenage Obesity Using Earlier Childhood Measurements from Millennium Cohort Study. ICCBDC 2023: 55-60 - [i3]Victor Elijah Adeyemo, Anna Palczewska, Ben Jones, Dan Weaving:
Identification of pattern mining algorithm for rugby league players positional groups separation based on movement patterns. CoRR abs/2302.14058 (2023) - 2022
- [c14]Jackie Campbell, Anna Palczewska, Ayotomide Adeyeye, Osayande Omobude, Windi Marva, Claire Griffiths, Paul Gately, Dorothy Monekosso:
Weight Management Programme: Use of Machine Learning Approaches to Identify Client Outcomes. UKCI 2022: 181-191 - [c13]Christopher Todd, Anna Palczewska, Dan Weaving:
Injury Risk Prediction in Rugby League Players with Training Volume Data and Machine Learning. UKCI 2022: 192-203 - [c12]Thomas Sawczuk, Anna Palczewska, Ben Jones, Jan Palczewski:
Use of Kernel Density Estimation to Understand the Spatial Trends of Attacking Possessions in Rugby League. UKCI 2022: 214-225 - 2021
- [j4]Justin Keen, Roy A. Ruddle, Jan Palczewski, Georgios Aivaliotis, Anna Palczewska, Christopher Megone, Kevin Macnish:
Machine learning, materiality and governance: A health and social care case study. Inf. Polity 26(1): 57-69 (2021) - [c11]Anna Palczewska
, Urszula Markowska-Kaczmar
:
Interpreting Neural Networks Prediction for a Single Instance via Random Forest Feature Contributions. ICCS (2) 2021: 140-153 - [c10]Victor Elijah Adeyemo
, Anna Palczewska, Ben Jones:
LCCspm: l-Length Closed Contiguous Sequential Patterns Mining Algorithm to Find Frequent Athlete Movement Patterns from GPS. ICMLA 2021: 455-460 - [c9]Thomas Sawczuk, Anna Palczewska, Ben Jones:
Markov Decision Processes with Contextual Nodes as a Method of Assessing Attacking Player Performance in Rugby League. UKCI 2021: 251-263 - [i2]Thomas Sawczuk, Anna Palczewska, Ben Jones:
Development of an expected possession value model to analyse team attacking performances in rugby league. CoRR abs/2105.05303 (2021) - 2020
- [c8]Oladapo Babajide, Hissam Tawfik, Anna Palczewska, Anatoliy Gorbenko, Arne Astrup
, J. Alfredo Martinez, Jean-Michel Oppert, Thorkild I. A. Sørensen:
A Machine Learning Approach to Short-Term Body Weight Prediction in a Dietary Intervention Program. ICCS (4) 2020: 441-455
2010 – 2019
- 2019
- [c7]Oladapo Babajide, Hissam Tawfik, Anna Palczewska, Anatoliy Gorbenko
, Arne Astrup
, J. Alfredo Martinez, Jean-Michel Oppert, Thorkild I. A. Sørensen:
Application of Unsupervised Learning in Weight-Loss Categorisation for Weight Management Programs. DESSERT 2019: 94-101 - 2017
- [j3]Richard Marchese Robinson
, Anna Palczewska, Jan Palczewski
, Nathan J. Kidley:
Comparison of the Predictive Performance and Interpretability of Random Forest and Linear Models on Benchmark Data Sets. J. Chem. Inf. Model. 57(8): 1773-1792 (2017) - [c6]Anna Palczewska, Jan Palczewski, Georgios Aivaliotis, Lukasz Kowalik
:
RobustSPAM for Inference from Noisy Longitudinal Data and Preservation of Privacy. ICMLA 2017: 344-351 - [c5]Remigiusz Kozlowski
, Anna Palczewska, Lukasz Borowiecki:
Analysis of Expanded Possibilities of ITS Systems Augmented with New Vision System Elements: The Case of Lodz. TST 2017: 333-343 - 2016
- [c4]Remigiusz Kozlowski
, Anna Palczewska, Jakub Jablonski:
The Scope and Capabilities of ITS - the Case of Lodz. TST 2016: 305-316 - 2014
- [c3]Pritesh Mistry, Anna Palczewska, Daniel Neagu
, Paul R. Trundle:
Using computational methods for the prediction of drug vehicles. UKCI 2014: 1-7 - 2013
- [j2]Anna Palczewska, Xin Fu, Paul R. Trundle, Longzhi Yang
, Daniel Neagu
, Mick J. Ridley, Kim Travis:
Towards model governance in predictive toxicology. Int. J. Inf. Manag. 33(3): 567-582 (2013) - [j1]Anna Palczewska, Daniel Neagu
, Mick J. Ridley:
Using Pareto points for model identification in predictive toxicology. J. Cheminformatics 5: 16 (2013) - [c2]Anna Palczewska, Jan Palczewski
, Richard Marchese Robinson
, Daniel Neagu
:
Interpreting random forest models using a feature contribution method. IRI 2013: 112-119 - [c1]Anna Palczewska, Jan Palczewski
, Richard Marchese Robinson
, Daniel Neagu
:
Interpreting Random Forest Classification Models Using a Feature Contribution Method. IRI (best papers) 2013: 193-218 - [i1]Anna Palczewska, Jan Palczewski, Richard Marchese Robinson, Daniel Neagu:
Interpreting random forest classification models using a feature contribution method. CoRR abs/1312.1121 (2013)
Coauthor Index
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last updated on 2024-05-26 00:44 CEST by the dblp team
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