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1Data mining in the Life Sciences with Random Forest: a walk in the park or lost in the jungle?
W. Touw, J. Bayjanov, L. Overmars, L. Backus, J. Boekhorst, M. Wels, and S. Hijum. Briefings in Bioinformatics, (July 2012)
8 years ago by @yourwelcome
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Learning,
algorithms,
Random
conditional
selection,
Forest,
interaction
model
importance,
variable
Machine
relationships,
Learning,algorithms,Randomconditionalselection,Forest,interactionmodelimportance,variableMachinerelationships,
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1High Fidelity Approximation of Slow Simulators Using Machine Learning for Real-time Simulation/Optimization
S. Regmi, L. Deschaine, and S. Regmi. 2004 Business and Industry Symposium, Washington, DC, USA, (April 2004)
17 years ago by @brazovayeye
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genetic
Learning,
Optimisation
algorithms,
programming,
Simulation,
Machine
geneticLearning,Optimisationalgorithms,programming,Simulation,Machine
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1Soft computing paradigms for hybrid fuzzy controllers: experiments and applications
M. Akbarzadeh-T., E. Tunstel, K. Kumbla, and M. Jamshidi. Proceedings of the 1998 IEEE World Congress on Computational Intelligence, 2, page 1200--1205. Anchorage, Alaska, USA, IEEE Press, (5-9 May 1998)
17 years ago by @brazovayeye
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algorithm-fuzzy
genetic
behavior-based
mobile
task
intelligence,
hybrid
flexible
networks,
machine
added
DC
drive
controller,
motor,
neural
ability,
controllers,
brushless
direct
learning
motors,
robots,
paradigms,
adaptation,
planning,
systems,
path
link,
algorithms,
programming-fuzzy
robot
manipulators,
computing
navigation
neurocontrollers,
hierarchical
programming,
schemes,
control,
soft
programs,
fuzzy
logic-based
algorithm-fuzzygeneticbehavior-basedmobiletaskintelligence,hybridflexiblenetworks,machineaddedDCdrivecontroller,motor,neuralability,controllers,brushlessdirectlearningmotors,robots,paradigms,adaptation,planning,systems,pathlink,algorithms,programming-fuzzyrobotmanipulators,computingnavigationneurocontrollers,hierarchicalprogramming,schemes,control,softprograms,fuzzylogic-based
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2Automated synthesis of a fixed-length loaded symmetric dipole antenna whose gain exceeds that of a commercial antenna and matches the theoretical maximum
J. Koza, S. Al-Sakran, L. Jones, and G. Manassero. GECCO '07: Proceedings of the 9th annual conference on Genetic and evolutionary computation, 2, page 2074--2081. London, ACM Press, (7-11 July 2007)
17 years ago by @brazovayeye
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genetic
design,
Real-World
result,
automated
algorithms,
programming,
machine
competitive
antenna,
human
invention
Applications,
geneticdesign,Real-Worldresult,automatedalgorithms,programming,machinecompetitiveantenna,humaninventionApplications,
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1Genetic Programming
J. Koza, and R. Poli. Search Methodologies: Introductory Tutorials in Optimization and Decision Support Techniques, chapter 5, Springer, (2005)
17 years ago by @brazovayeye
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human-competitive
genetic
schema
algorithms,
intelligence,
learning,
programming,
machine
theory
human-competitivegeneticschemaalgorithms,intelligence,learning,programming,machinetheory
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1Adapting genetic regulatory models by genetic programming
R. Eriksson, and B. Olsson. Biosystems, 76 (1-3): 217--227 (2004)
17 years ago by @brazovayeye
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genetic
algorithms,
Gene
networks,
programming,
Evolutionary
learning
Machine
geneticalgorithms,Genenetworks,programming,EvolutionarylearningMachine
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1A Genetic Programming Tutorial
J. Koza, and R. Poli. www, (2003)
17 years ago by @brazovayeye
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human-competitive
genetic
schema
algorithms,
intelligence,
learning,
programming,
machine
theory
human-competitivegeneticschemaalgorithms,intelligence,learning,programming,machinetheory
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1Genetic Programming
H. Hirsh, W. Banzhaf, J. Koza, C. Ryan, L. Spector, and C. Jacob. IEEE Intelligent Systems, 15 (3): 74--84 (May 2000)
17 years ago by @brazovayeye
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genetic
code
processes
automatic
arbitrary
artificial
algorithms,
computer
evolution,
intelligence,
programming,
machine
computational
geneticcodeprocessesautomaticarbitraryartificialalgorithms,computerevolution,intelligence,programming,machinecomputational
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1Routine high-return human-competitive machine learning
J. Koza. Proceedings of the International Conference on Machine Learning and Applications, page 6--12. Los Angeles, (2003)
17 years ago by @brazovayeye
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human-competitive
genetic
topology,
algorithms,
parameterized
learning,
programming,
machine
automated
invention,
human-competitivegenetictopology,algorithms,parameterizedlearning,programming,machineautomatedinvention,
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publications (hide)9
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1Data mining in the Life Sciences with Random Forest: a walk in the park or lost in the jungle?

1High Fidelity Approximation of Slow Simulators Using Machine Learning for Real-time Simulation/Optimization

1Soft computing paradigms for hybrid fuzzy controllers: experiments and applications

2Automated synthesis of a fixed-length loaded symmetric dipole antenna whose gain exceeds that of a commercial antenna and matches the theoretical maximum

1Genetic Programming

1Adapting genetic regulatory models by genetic programming

1A Genetic Programming Tutorial

1Genetic Programming

1Routine high-return human-competitive machine learning

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