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ISBN 10: 3209037205ISBN 13: 9783209037206
Anbieter: medimops, Berlin, Deutschland
Buch
Gut/Very good: Buch bzw. Schutzumschlag mit wenigen Gebrauchsspuren an Einband, Schutzumschlag oder Seiten. / Describes a book or dust jacket that does show some signs of wear on either the binding, dust jacket or pages.
Verlag: Leipzig, 1999, 1999
Anbieter: Antiquariaat Pieter Judo (De Lezenaar), Hasselt, Belgien
Verbandsmitglied: ILAB
234 + 4 + 52pp., with 61 bl/w ills., 21cm., softcover, text in German, Doctoral dissertation (Von der Fakultät für Geschichte, Kunst- und Orientwissenschaften der Universität Leipzig angenommene Dissertation zur Erlangung des akademischen Grades Doctor Philosophiae), stamp at verso of title page, text is clean and bright (looks unread), good condition, X110812.
Verlag: Springer New York, 2014
ISBN 10: 1489989633ISBN 13: 9781489989635
Anbieter: AHA-BUCH GmbH, Einbeck, Deutschland
Buch
Taschenbuch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - Every mathematical discipline goes through three periods of development: the naive, the formal, and the critical. David Hilbert The goal of this book is to explain the principles that made support vector machines (SVMs) a successful modeling and prediction tool for a variety of applications. We try to achieve this by presenting the basic ideas of SVMs together with the latest developments and current research questions in a uni ed style. In a nutshell, we identify at least three reasons for the success of SVMs: their ability to learn well with only a very small number of free parameters, their robustness against several types of model violations and outliers, and last but not least their computational e ciency compared with several other methods. Although there are several roots and precursors of SVMs, these methods gained particular momentum during the last 15 years since Vapnik (1995, 1998) published his well-known textbooks on statistical learning theory with aspecialemphasisonsupportvectormachines. Sincethen,the eldofmachine learninghaswitnessedintenseactivityinthestudyofSVMs,whichhasspread moreandmoretootherdisciplinessuchasstatisticsandmathematics. Thusit seems fair to say that several communities are currently working on support vector machines and on related kernel-based methods. Although there are many interactions between these communities, we think that there is still roomforadditionalfruitfulinteractionandwouldbegladifthistextbookwere found helpful in stimulating further research. Many of the results presented in this book have previously been scattered in the journal literature or are still under review. As a consequence, these results have been accessible only to a relativelysmallnumberofspecialists,sometimesprobablyonlytopeoplefrom one community but not the others.
Verlag: Springer New York, 2008
ISBN 10: 0387772413ISBN 13: 9780387772417
Anbieter: AHA-BUCH GmbH, Einbeck, Deutschland
Buch
Buch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - Every mathematical discipline goes through three periods of development: the naive, the formal, and the critical. David Hilbert The goal of this book is to explain the principles that made support vector machines (SVMs) a successful modeling and prediction tool for a variety of applications. We try to achieve this by presenting the basic ideas of SVMs together with the latest developments and current research questions in a uni ed style. In a nutshell, we identify at least three reasons for the success of SVMs: their ability to learn well with only a very small number of free parameters, their robustness against several types of model violations and outliers, and last but not least their computational e ciency compared with several other methods. Although there are several roots and precursors of SVMs, these methods gained particular momentum during the last 15 years since Vapnik (1995, 1998) published his well-known textbooks on statistical learning theory with aspecialemphasisonsupportvectormachines. Sincethen,the eldofmachine learninghaswitnessedintenseactivityinthestudyofSVMs,whichhasspread moreandmoretootherdisciplinessuchasstatisticsandmathematics. Thusit seems fair to say that several communities are currently working on support vector machines and on related kernel-based methods. Although there are many interactions between these communities, we think that there is still roomforadditionalfruitfulinteractionandwouldbegladifthistextbookwere found helpful in stimulating further research. Many of the results presented in this book have previously been scattered in the journal literature or are still under review. As a consequence, these results have been accessible only to a relativelysmallnumberofspecialists,sometimesprobablyonlytopeoplefrom one community but not the others.
Verlag: Mainz: Hermann Schmidt, 1997
Anbieter: Gloria Mortzeck, Karlsdorf, Deutschland
264 S. 4°, OLn. kasch., OU an oberer Kante etw. angestoßen, sonst fast neuwertiger Zustand. Frontispiz: Porträt Prof. Imiela. Sehr schöne typografische Buchgestaltung. 1400 gr.
Verlag: Wien : öbv & hpt, 2003
ISBN 10: 3209037205ISBN 13: 9783209037206
Buch Erstausgabe
29,5 x 20,5 cm. Zustand: Gut. 1. Auflage. 232 Seiten.; Durchgehend mit Abbildungen Original Broschur mit Bibliotheksrückenschild. Leicht berieben. Innen mit den übl. Bibliotheksstempeln- u. Einträgen, teils durchgestrichen, sehr sauberes Exemplar. B16-03-03B|S19 Sprache: Deutsch Gewicht in Gramm: 650.
Verlag: EB-Verlag, 2012
ISBN 10: 3868930574ISBN 13: 9783868930573
Anbieter: Studibuch, Stuttgart, Deutschland
Buch
hardcover. Zustand: Gut. 423 Seiten; 9783868930573.3 Sprache: Deutsch Gewicht in Gramm: 2.