A Genetic Programming Approach to Feature Selection
and Classification of Instantaneous Cognitive States
R. Ramirez, and M. Puiggros. Applications of Evolutionary Computing,
EvoWorkshops2007: EvoCOMNET, EvoFIN, EvoIASP,
EvoInteraction, EvoMUSART, EvoSTOC,
EvoTransLog, volume 4448 of LNCS, page 311--319. Valencia, Spain, Springer Verlag, (11-13 April 2007)
DOI: doi:10.1007/978-3-540-71805-5_34
Abstract
The study of human brain functions has dramatically
increased in recent years greatly due to the advent of
Functional Magnetic Resonance Imaging. This paper
presents a genetic programming approach to the problem
of classifying the instantaneous cognitive state of a
person based on his/her functional Magnetic Resonance
Imaging data. The problem provides a very interesting
case study of training classifiers with extremely high
dimensional, sparse and noisy data. We apply genetic
programming for both feature selection and classifier
training. We present a successful case study of induced
classifiers which accurately discriminate between
cognitive states produced by listening to different
auditory stimuli.
%0 Conference Paper
%1 ramirez:evows07
%A Ramirez, Rafael
%A Puiggros, Montserrat
%B Applications of Evolutionary Computing,
EvoWorkshops2007: EvoCOMNET, EvoFIN, EvoIASP,
EvoInteraction, EvoMUSART, EvoSTOC,
EvoTransLog
%C Valencia, Spain
%D 2007
%E Giacobini, Mario
%E Brabazon, Anthony
%E Cagnoni, Stefano
%E Di Caro, Gianni A.
%E Drechsler, Rolf
%E Farooq, Muddassar
%E Fink, Andreas
%E Lutton, Evelyne
%E Machado, Penousal
%E Minner, Stefan
%E O'Neill, Michael
%E Romero, Juan
%E Rothlauf, Franz
%E Squillero, Giovanni
%E Takagi, Hideyuki
%E Uyar, A. Sima
%E Yang, Shengxiang
%I Springer Verlag
%K algorithms, data extraction, fMRI feature genetic programming,
%P 311--319
%R doi:10.1007/978-3-540-71805-5_34
%T A Genetic Programming Approach to Feature Selection
and Classification of Instantaneous Cognitive States
%V 4448
%X The study of human brain functions has dramatically
increased in recent years greatly due to the advent of
Functional Magnetic Resonance Imaging. This paper
presents a genetic programming approach to the problem
of classifying the instantaneous cognitive state of a
person based on his/her functional Magnetic Resonance
Imaging data. The problem provides a very interesting
case study of training classifiers with extremely high
dimensional, sparse and noisy data. We apply genetic
programming for both feature selection and classifier
training. We present a successful case study of induced
classifiers which accurately discriminate between
cognitive states produced by listening to different
auditory stimuli.
@inproceedings{ramirez:evows07,
abstract = {The study of human brain functions has dramatically
increased in recent years greatly due to the advent of
Functional Magnetic Resonance Imaging. This paper
presents a genetic programming approach to the problem
of classifying the instantaneous cognitive state of a
person based on his/her functional Magnetic Resonance
Imaging data. The problem provides a very interesting
case study of training classifiers with extremely high
dimensional, sparse and noisy data. We apply genetic
programming for both feature selection and classifier
training. We present a successful case study of induced
classifiers which accurately discriminate between
cognitive states produced by listening to different
auditory stimuli.},
added-at = {2008-06-19T17:35:00.000+0200},
address = {Valencia, Spain},
author = {Ramirez, Rafael and Puiggros, Montserrat},
biburl = {https://www.bibsonomy.org/bibtex/2eb6b7816fee9cefe0a7031a226b08974/brazovayeye},
booktitle = {Applications of Evolutionary Computing,
EvoWorkshops2007: {EvoCOMNET}, {EvoFIN}, {EvoIASP},
{EvoInteraction}, {EvoMUSART}, {EvoSTOC},
{EvoTransLog}},
doi = {doi:10.1007/978-3-540-71805-5_34},
editor = {Giacobini, Mario and Brabazon, Anthony and Cagnoni, Stefano and {Di Caro}, Gianni A. and Drechsler, Rolf and Farooq, Muddassar and Fink, Andreas and Lutton, Evelyne and Machado, Penousal and Minner, Stefan and O'Neill, Michael and Romero, Juan and Rothlauf, Franz and Squillero, Giovanni and Takagi, Hideyuki and Uyar, A. Sima and Yang, Shengxiang},
interhash = {27941ac94156a5a760f88fe0746ece00},
intrahash = {eb6b7816fee9cefe0a7031a226b08974},
isbn13 = {978-3-540-71804-8},
keywords = {algorithms, data extraction, fMRI feature genetic programming,},
month = {11-13 April},
notes = {EvoWorkshops2007},
pages = {311--319},
publisher = {Springer Verlag},
series = {LNCS},
timestamp = {2008-06-19T17:50:06.000+0200},
title = {A Genetic Programming Approach to Feature Selection
and Classification of Instantaneous Cognitive States},
volume = 4448,
year = 2007
}