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Kategorie szczegółowe BISAC

Agent and Multi-Agent Systems: Technologies and Applications: 4th KES International Symposium, KES-AMSTA 2010, Gdynia, Poland, June 23-25, 2010. Proceedings, Part II

ISBN-13: 9783642135408 / Angielski / Miękka / 2010 / 443 str.

Piotr Jedrzejowicz;Ngoc-Thanh Nguyen;Robert J. Howlett
Agent and Multi-Agent Systems: Technologies and Applications: 4th KES International Symposium, KES-AMSTA 2010, Gdynia, Poland, June 23-25, 2010. Proceedings, Part II Piotr Jedrzejowicz, Ngoc-Thanh Nguyen, Robert J. Howlett, Lakhmi C Jain 9783642135408 Springer-Verlag Berlin and Heidelberg GmbH &  - książkaWidoczna okładka, to zdjęcie poglądowe, a rzeczywista szata graficzna może różnić się od prezentowanej.

Agent and Multi-Agent Systems: Technologies and Applications: 4th KES International Symposium, KES-AMSTA 2010, Gdynia, Poland, June 23-25, 2010. Proceedings, Part II

ISBN-13: 9783642135408 / Angielski / Miękka / 2010 / 443 str.

Piotr Jedrzejowicz;Ngoc-Thanh Nguyen;Robert J. Howlett
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Presented experiments show that usage ofevolutionary approach to feature - duction is justi?ed.Feature selection as well as construction gives goodresults. It is noticeable that attribute construction s best results assign higher classi?- tion accuracy than feature selection alone.That is why, carrying out selection before construction to decrease searchingspace isagoodsolution. Because of indeterministicbehavior of neuralnetworks, it was di?cultto - ducefeaturesetincaseofusingthemto evaluatecandidateresults.Forexample, aneuralnetworklearntverywellondatathatwasdescribedbyfullattributeset, but when thisset was decreased it had huge problems to do this duringrequired number ofepochs.That suggests that usingC4.5 ismuchmore preferred. Numerous experiments havebeen performed and observed.Analysis ofabove results allowsto put the hypothesisthat it is worth to use Construction module as the feature set reduction. But experiments show that Constructormodule does not work sowell whenitusesthe whole initial set offeatures the search space istoo large.Soit is worth to use ?rstly Selectorand nextConstructor. The second important issue isthatConstructor destructs the semanticmeaning of the features.New constructed features are notunderstandableforusers.In some real-liveproblems measuring offeature values isquite expensive, forsuch problems selector seems to be more suitable because itdiminishes a number of realfeatures.To constructonefeaturesa number ofreal(measured)featurescan be required. Obtainedresults haveencouragedus to extendour system, especiallythe c- structormodule.Weplan to developenlarged set offunctionsFwhich allowsto use the system with data containingdi?erenttype offeatures, not only nume- cal. Such system will be veri?ed usingagreater number ofbenchmark data sets as well as real data. Acknowledgments. This work ispartially ?nanced fromthe Ministryof S- ence and Higher Education Republic of Polandresources in 2008 2010 years as a Poland Singapore joint research project 65/N-SINGAPORE/2007/0."

Kategorie:
Informatyka, Bazy danych
Kategorie BISAC:
Computers > Artificial Intelligence - General
Computers > Data Science - Data Analytics
Computers > System Administration - Storage & Retrieval
Wydawca:
Springer-Verlag Berlin and Heidelberg GmbH &
Seria wydawnicza:
Lecture Notes in Artificial Intelligence
Język:
Angielski
ISBN-13:
9783642135408
Rok wydania:
2010
Dostępne języki:
Angielski
Wydanie:
2010
Numer serii:
000304238
Ilość stron:
443
Waga:
0.65 kg
Oprawa:
Miękka
Wolumenów:
01

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