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Applications of Supervised and Unsupervised Ensemble Methods (Hardcover, 2010 ed.)
Loot Price: R2,828
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Applications of Supervised and Unsupervised Ensemble Methods (Hardcover, 2010 ed.)
Series: Studies in Computational Intelligence, 245
Expected to ship within 10 - 15 working days
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This book contains the extended papers presented at the 2nd
Workshop on Supervised and Unsupervised Ensemble Methods and their
Applications
(SUEMA)heldon21-22July,2008inPatras,Greece,inconjunctionwiththe
18thEuropeanConferenceon Arti?cial Intelligence(ECAI 2008). This
wo- shop was a successor of the smaller event held in 2007 in
conjunction with 3rd Iberian Conference on Pattern Recognition and
Image Analysis, Girona, Spain. The success of that event as well as
the publication of workshop - pers in the edited book "Supervised
and Unsupervised Ensemble Methods and their Applications",
published by Springer-Verlag in Studies in Com- tational
Intelligence Series in volume 126, encouraged us to continue a good
tradition. The scope of both SUEMA workshops (hence, the book as
well) is the application of theoretical ideas in the ?eld of
ensembles of classi?cation and
clusteringalgorithmstoreal/lifeproblemsinscienceandindustry.
Ensembles, which represent a number of algorithms whose class or
cluster membership predictions are combined together to produce a
single outcome value, have alreadyprovedto be a viable
alternativeto a single best algorithmin various practical tasks
under di?erent scenarios, from bioinformatics to biometrics, from
medicine to network security. The ensemble approach is caused to
life by the famous "no free lunch" theorem, stating that there is
no absolutely best algorithm to solve all problems. Although
ensembles cannot be cons- ered as absolute remedy of a single
algorithm de?ciency, it is widely believed
thatensemblesprovideabetteranswerto"nofreelunch"theoremthanas-
glebestalgorithm.
Statistical,algorithmical,representational,computational and
practical reasons can explain the success of ensemble methods.
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