%0 Book Section %1 Saetrom:2006:GPTP %A Saetrom, Pal %A Birkeland, Olaf Rene %A Snove Jr., Ola %B Genetic Programming Theory and Practice IV %C Ann Arbor %D 2006 %E Riolo, Rick L. %E Soule, Terence %E Worzel, Bill %I Springer %K Bioinformatics, RNAi algorithms, gene genetic microRNA, prediction, programming, %P - %T Boosting improves stability and accuracy of genetic programming in biological classification %V 5 %X Biological sequence analysis presents interesting challenges for machine learning. Using one of the most important current problems -- the recognition of functional target sites for microRNA molecules -- as an example, we show how joining multiple genetic programming classifiers improves accuracy and stability tremendously. When moving from single classifiers to bagging and boosting with cross validation and parameter optimisation, you require more computing power. We use a special-purpose search processor for fitness evaluation, which renders boosted genetic programming practical for our purposes. %& 18 %@ 0-387-33375-4

@incollection{Saetrom:2006:GPTP, abstract = {Biological sequence analysis presents interesting challenges for machine learning. Using one of the most important current problems -- the recognition of functional target sites for microRNA molecules -- as an example, we show how joining multiple genetic programming classifiers improves accuracy and stability tremendously. When moving from single classifiers to bagging and boosting with cross validation and parameter optimisation, you require more computing power. We use a special-purpose search processor for fitness evaluation, which renders boosted genetic programming practical for our purposes.}, added-at = {2008-06-19T17:46:40.000+0200}, address = {Ann Arbor}, author = {Saetrom, Pal and Birkeland, Olaf Rene and {Snove Jr.}, Ola}, biburl = {https://www.bibsonomy.org/bibtex/2491a43838cb4a9eee10fc5a5d9a02b39/brazovayeye}, booktitle = {Genetic Programming Theory and Practice {IV}}, chapter = 18, editor = {Riolo, Rick L. and Soule, Terence and Worzel, Bill}, interhash = {18c8429579ad481a52b30f100625fcd9}, intrahash = {491a43838cb4a9eee10fc5a5d9a02b39}, isbn = {0-387-33375-4}, keywords = {Bioinformatics, RNAi algorithms, gene genetic microRNA, prediction, programming,}, month = {11-13 May}, notes = {part of \cite{Riolo:2006:GPTP} Published Jan 2007 after the workshop}, pages = {-}, publisher = {Springer}, series = {Genetic and Evolutionary Computation}, size = {16 pages}, timestamp = {2008-06-19T17:50:55.000+0200}, title = {Boosting improves stability and accuracy of genetic programming in biological classification}, volume = 5, year = 2006 }