Ryan J Urbanowicz
Title
Cited by
Cited by
Year
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
3672018
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
3032016
Learning classifier systems: a complete introduction, review, and roadmap
RJ Urbanowicz, JH Moore
Journal of Artificial Evolution and Applications 2009, 2009
2882009
TPOT: A tree-based pipeline optimization tool for automating machine learning
RS Olson, JH Moore
Workshop on automatic machine learning, 66-74, 2016
2722016
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
1912016
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), 1-13, 2017
1742017
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
1652012
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
982018
Analysis of gene‐gene interactions
D Gilbert‐Diamond, JH Moore
Current protocols in human genetics 70 (1), 1.14. 1-1.14. 12, 2011
672011
Applications of Evolutionary Computation: 19th European Conference, EvoApplications 2016, Porto, Portugal, March 30--April 1, 2016, Proceedings, Part I
G Squillero, P Burelli
Springer, 2016
632016
ExSTraCS 2.0: description and evaluation of a scalable learning classifier system
RJ Urbanowicz, JH Moore
Evolutionary intelligence 8 (2), 89-116, 2015
632015
Introduction to learning classifier systems
RJ Urbanowicz, WN Browne
Springer, 2017
602017
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
522013
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
462012
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
382010
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
362012
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), 1-13, 2012
322012
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
252012
Statistical inference Relief (STIR) feature selection
TT Le, RJ Urbanowicz, JH Moore, BA McKinney
Bioinformatics 35 (8), 1358-1365, 2019
222019
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
212014
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