TY - JOUR
T1 - Evolutionary algorithms for data mining
AU - COLLET, Poierre
AU - WONG, Man Leung
PY - 2012/3
Y1 - 2012/3
N2 - Artificial evolution can be applied to machine learning thanks to genetic programming, for instance, which is a very successful branch of Evolutionary Computing. One would therefore think that by transitivity, because data-mining is one of the main applications of machine learning, artificial evolution could be successful in solving data-mining problems. Whether this is the case or not, it seems that artificial evolution is not much used in data-mining, even though many papers show that EC can provide interesting alternative solutions to standard machine learning approaches.
AB - Artificial evolution can be applied to machine learning thanks to genetic programming, for instance, which is a very successful branch of Evolutionary Computing. One would therefore think that by transitivity, because data-mining is one of the main applications of machine learning, artificial evolution could be successful in solving data-mining problems. Whether this is the case or not, it seems that artificial evolution is not much used in data-mining, even though many papers show that EC can provide interesting alternative solutions to standard machine learning approaches.
UR - http://commons.ln.edu.hk/sw_master/2546
UR - http://www.scopus.com/inward/record.url?scp=84861101531&partnerID=8YFLogxK
U2 - 10.1007/s10710-011-9156-z
DO - 10.1007/s10710-011-9156-z
M3 - Journal Article (refereed)
SN - 1389-2576
VL - 13
SP - 69
EP - 70
JO - Genetic Programming and Evolvable Machines
JF - Genetic Programming and Evolvable Machines
IS - 1
ER -