Tuning Metaheuristics: A Machine Learning Perspective (Studies in Computational Intelligence)
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1
Tuning Metaheuristics: A Machine Learning Perspective (Studies in Computational Intelligence) (2009)
EN NW FE EB DLISBN: 9783642004834 bzw. 3642004830, in Englisch, 221 Seiten, Springer, neu, Erstausgabe, E-Book, elektronischer Download.
Lieferung aus: Deutschland, E-Book zum Download, Versandkostenfrei.
This book lays the foundations for a scientific approach to tuning metaheuristics. The fundamental intuition that underlies Birattari's approach is that the tuning problem has much in common with the problems that are typically faced in machine learning., Kindle Edition, Ausgabe: 1st ed. 2005. 2nd printing 2009, Format: Kindle eBook, Label: Springer, Springer, Produktgruppe: eBooks, Publiziert: 2009-05-02, Freigegeben: 2009-05-02, Studio: Springer.
This book lays the foundations for a scientific approach to tuning metaheuristics. The fundamental intuition that underlies Birattari's approach is that the tuning problem has much in common with the problems that are typically faced in machine learning., Kindle Edition, Ausgabe: 1st ed. 2005. 2nd printing 2009, Format: Kindle eBook, Label: Springer, Springer, Produktgruppe: eBooks, Publiziert: 2009-05-02, Freigegeben: 2009-05-02, Studio: Springer.
2
Tuning Metaheuristics
DE NWISBN: 9783642004834 bzw. 3642004830, in Deutsch, Springer Berlin, neu.
Lieferung aus: Deutschland, sofort lieferbar.
The importance of tuning metaheuristics is widely acknowledged in scientific literature. However, there is very little dedicated research on the subject. Typically, scientists and practitioners tune metaheuristics by hand, guided only by their experience and by some rules of thumb. Tuning metaheuristics is often considered to be more of an art than a science.This book lays the foundations for a scientific approach to tuning metaheuristics. The fundamental intuition that underlies Birattari's approach is that the tuning problem has much in common with the problems that are typically faced in machine learning. By adopting a machine learning perspective, the author gives a formal definition of the tuning problem, develops a generic algorithm for tuning metaheuristics, and defines an appropriate experimental methodology for assessing the performance of metaheuristics.
The importance of tuning metaheuristics is widely acknowledged in scientific literature. However, there is very little dedicated research on the subject. Typically, scientists and practitioners tune metaheuristics by hand, guided only by their experience and by some rules of thumb. Tuning metaheuristics is often considered to be more of an art than a science.This book lays the foundations for a scientific approach to tuning metaheuristics. The fundamental intuition that underlies Birattari's approach is that the tuning problem has much in common with the problems that are typically faced in machine learning. By adopting a machine learning perspective, the author gives a formal definition of the tuning problem, develops a generic algorithm for tuning metaheuristics, and defines an appropriate experimental methodology for assessing the performance of metaheuristics.
3
Tuning Metaheuristics
DE NWISBN: 9783642004834 bzw. 3642004830, in Deutsch, Springer Berlin, neu.
Lieferung aus: Deutschland, sofort lieferbar.
2009, Englisch, The importance of tuning metaheuristics is widely acknowledged in scientific literature. However, there is very little dedicated research on the subject. Typically, scientists and practitioners tune metaheuristics by hand, guided only by their experience and by some rules of thumb. Tuning metaheuristics is often considered to be more of an art than a science.This book lays the foundations for a scientific approach to tuning metaheuristics. The fundamental intuition that underlies Birattari's approach is that the tuning problem has much in common with the problems that are typically faced in machine learning. By adopting a machine learning perspective, the author gives a formal definition of the tuning problem, develops a generic algorithm for tuning metaheuristics, and defines an appropriate experimental methodology for assessing the performance of metaheuristics.
2009, Englisch, The importance of tuning metaheuristics is widely acknowledged in scientific literature. However, there is very little dedicated research on the subject. Typically, scientists and practitioners tune metaheuristics by hand, guided only by their experience and by some rules of thumb. Tuning metaheuristics is often considered to be more of an art than a science.This book lays the foundations for a scientific approach to tuning metaheuristics. The fundamental intuition that underlies Birattari's approach is that the tuning problem has much in common with the problems that are typically faced in machine learning. By adopting a machine learning perspective, the author gives a formal definition of the tuning problem, develops a generic algorithm for tuning metaheuristics, and defines an appropriate experimental methodology for assessing the performance of metaheuristics.
4
Tuning Metaheuristics
DE NWISBN: 9783642004834 bzw. 3642004830, in Deutsch, Springer, Berlin/Heidelberg/New York, NY, Deutschland, neu.
Lieferung aus: Vereinigtes Königreich Großbritannien und Nordirland, Versandkostenfrei.
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Die Beschreibung dieses Angebotes ist von geringer Qualität oder in einer Fremdsprache. Trotzdem anzeigen
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