Ryan J Urbanowicz
TitleCited byYear
Learning classifier systems: a complete introduction, review, and roadmap
RJ Urbanowicz, JH Moore
Journal of Artificial Evolution and Applications 2009, 2009
2432009
Evaluation of a tree-based pipeline optimization tool for automating data science
RS Olson, N Bartley, RJ Urbanowicz, JH Moore
Proceedings of the Genetic and Evolutionary Computation Conference 2016, 485-492, 2016
1502016
GAMETES: a fast, direct algorithm for generating pure, strict, epistatic models with random architectures
RJ Urbanowicz, J Kiralis, NA Sinnott-Armstrong, T Heberling, JM Fisher, ...
BioData mining 5 (1), 1-14, 2012
1322012
Relief-based feature selection: Introduction and review
RJ Urbanowicz, M Meeker, W La Cava, RS Olson, JH Moore
Journal of biomedical informatics 85, 189-203, 2018
1232018
Automating biomedical data science through tree-based pipeline optimization
RS Olson, RJ Urbanowicz, PC Andrews, NA Lavender, JH Moore
European Conference on the Applications of Evolutionary Computation, 123-137, 2016
1022016
TPOT: A tree-based pipeline optimization tool for automating machine learning
RS Olson, JH Moore
Automated Machine Learning, 151-160, 2019
902019
PMLB: a large benchmark suite for machine learning evaluation and comparison
RS Olson, W La Cava, P Orzechowski, RJ Urbanowicz, JH Moore
BioData mining 10 (1), 36, 2017
812017
Analysis of gene‐gene interactions
D Gilbert‐Diamond, JH Moore
Current protocols in human genetics 70 (1), 1.14. 1-1.14. 12, 2011
472011
Applications of Evolutionary Computation: 19th European Conference, EvoApplications 2016, Porto, Portugal, March 30--April 1, 2016, Proceedings
G Squillero, P Burelli
Springer, 2016
442016
Role of genetic heterogeneity and epistasis in bladder cancer susceptibility and outcome: a learning classifier system approach
RJ Urbanowicz, AS Andrew, MR Karagas, JH Moore
Journal of the American Medical Informatics Association 20 (4), 603-612, 2013
402013
An analysis pipeline with statistical and visualization-guided knowledge discovery for michigan-style learning classifier systems
RJ Urbanowicz, A Granizo-Mackenzie, JH Moore
IEEE computational intelligence magazine 7 (4), 35-45, 2012
402012
ExSTraCS 2.0: description and evaluation of a scalable learning classifier system
RJ Urbanowicz, JH Moore
Evolutionary intelligence 8 (2-3), 89-116, 2015
382015
The application of michigan-style learning classifiersystems to address genetic heterogeneity and epistasisin association studies
RJ Urbanowicz, JH Moore
Proceedings of the 12th annual conference on Genetic and evolutionary …, 2010
332010
Benchmarking relief-based feature selection methods for bioinformatics data mining
RJ Urbanowicz, RS Olson, P Schmitt, M Meeker, JH Moore
Journal of biomedical informatics 85, 168-188, 2018
322018
Predicting the difficulty of pure, strict, epistatic models: metrics for simulated model selection
RJ Urbanowicz, J Kiralis, JM Fisher, JH Moore
BioData mining 5 (1), 15, 2012
302012
Instance-linked attribute tracking and feedback for michigan-style supervised learning classifier systems
R Urbanowicz, A Granizo-Mackenzie, J Moore
Proceedings of the 14th annual conference on Genetic and evolutionary …, 2012
302012
Introduction to learning classifier systems
RJ Urbanowicz, WN Browne
Springer, 2017
282017
Using expert knowledge to guide covering and mutation in a michigan style learning classifier system to detect epistasis and heterogeneity
RJ Urbanowicz, D Granizo-Mackenzie, JH Moore
International Conference on Parallel Problem Solving from Nature, 266-275, 2012
222012
An extended michigan-style learning classifier system for flexible supervised learning, classification, and data mining
RJ Urbanowicz, G Bertasius, JH Moore
International Conference on Parallel Problem Solving from Nature, 211-221, 2014
182014
Rapid rule compaction strategies for global knowledge discovery in a supervised learning classifier system
J Tan, J Moore, R Urbanowicz
Artificial Life Conference Proceedings 13, 110-117, 2013
142013
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