passa ai contenuti
Boosting : foundations and algorithms Anteprima di questo documento
ChiudiAnteprima di questo documento
Stiamo controllando…

Boosting : foundations and algorithms

Autore: Robert E Schapire; Yoav Freund
Editore: Cambridge, MA : MIT Press, ©2012.
Serie: Adaptive computation and machine learning.
Edizione/Formato:   eBook : Document : EnglishVedi tutte le edizioni e i formati
Banca dati:WorldCat
Sommario:
A remarkably rich theory has evolved around boosting, with connections to a range of topics including statistics, game theory, convex optimization, and information geometry. Boosting algorithms have also enjoyed practical success in such fields as biology, vision, and speech processing. At various times in its history, boosting has been perceived as mysterious, controversial, even paradoxical. This book, written by  Per saperne di più…
Voto:

(non ancora votato) 0 con commenti - Diventa il primo.

Soggetti
Altri come questo

 

Trova una copia online

Collegamenti a questo documento

Trova una copia in biblioteca

&AllPage.SpinnerRetrieving; Stiamo ricercando le biblioteche che possiedono questo documento…

Dettagli

Genere/forma: Electronic books
Informazioni aggiuntive sul formato: Print version:
Schapire, Robert E.
Boosting.
Cambridge, MA : MIT Press, c2012
(DLC) 2011038972
(OCoLC)758388404
Tipo materiale: Document, Risorsa internet
Tipo documento: Internet Resource, Computer File
Tutti gli autori / Collaboratori: Robert E Schapire; Yoav Freund
ISBN: 9780262301183 0262301180
Numero OCLC: 794669892
Descrizione: 1 online resource (xv, 526 p.) : ill.
Contenuti: Foundations of machine learning --
Using AdaBoost to minimize training error --
Direct bounds on the generalization error --
The margins explanation for boosting's effectiveness --
Game theory, online learning, and boosting --
Loss minimization and generalizations of boosting --
Boosting, convex optimization, and information geometry --
Using confidence-rated weak predictions --
Multiclass classification problems --
Learning to rank --
Attaining the best possible accuracy --
Optimally efficient boosting --
Boosting in continuous time.
Titolo della serie: Adaptive computation and machine learning.
Responsabilità: Robert E. Schapire and Yoav Freund.

Abstract:

A remarkably rich theory has evolved around boosting, with connections to a range of topics including statistics, game theory, convex optimization, and information geometry. Boosting algorithms have also enjoyed practical success in such fields as biology, vision, and speech processing. At various times in its history, boosting has been perceived as mysterious, controversial, even paradoxical. This book, written by the inventors of the method, brings together, organizes, simplifies, and substantially extends two decades of research on boosting, presenting both theory and applications in a way that is accessible to readers from diverse backgrounds while also providing an authoritative reference for advanced researchers. With its introductory treatment of all material and its inclusion of exercises in every chapter, the book is appropriate for course use as well. --

Commenti

Recensioni editoriali

Sinossi editore

This excellent book is a mind-stretcher that should be read and reread, even by nonspecialists. Computing Reviews Boosting is, quite simply, one of the best-written books I've read on machine Per saperne di più…

 
Commenti degli utenti
Recuperando commenti GoodReads…
Stiamo recuperando commenti DOGObooks

Etichette

Diventa il primo.
Conferma questa richiesta

Potresti aver già richiesto questo documento. Seleziona OK se si vuole procedere comunque con questa richiesta.

Dati collegati


Primary Entity

<http://www.worldcat.org/oclc/794669892> # Boosting foundations and algorithms
    a schema:Book, schema:MediaObject, schema:CreativeWork ;
    library:oclcnum "794669892" ;
    library:placeOfPublication <http://experiment.worldcat.org/entity/work/data/1032229637#Place/cambridge_ma> ; # Cambridge, MA
    library:placeOfPublication <http://id.loc.gov/vocabulary/countries/mau> ;
    schema:about <http://id.worldcat.org/fast/1893023> ; # Boosting (Algorithms)
    schema:about <http://id.worldcat.org/fast/1139041> ; # Supervised learning (Machine learning)
    schema:about <http://experiment.worldcat.org/entity/work/data/1032229637#Topic/computers_enterprise_applications_business_intelligence_tools> ; # COMPUTERS / Enterprise Applications / Business Intelligence Tools
    schema:about <http://dewey.info/class/006.31/e23/> ;
    schema:about <http://experiment.worldcat.org/entity/work/data/1032229637#Topic/computers_intelligence_ai_&_semantics> ; # COMPUTERS / Intelligence (AI) & Semantics
    schema:bookFormat schema:EBook ;
    schema:contributor <http://viaf.org/viaf/63543180> ; # Yoav Freund
    schema:copyrightYear "2012" ;
    schema:creator <http://viaf.org/viaf/46940747> ; # Robert E. Schapire
    schema:datePublished "2012" ;
    schema:description "Foundations of machine learning -- Using AdaBoost to minimize training error -- Direct bounds on the generalization error -- The margins explanation for boosting's effectiveness -- Game theory, online learning, and boosting -- Loss minimization and generalizations of boosting -- Boosting, convex optimization, and information geometry -- Using confidence-rated weak predictions -- Multiclass classification problems -- Learning to rank -- Attaining the best possible accuracy -- Optimally efficient boosting -- Boosting in continuous time."@en ;
    schema:description "A remarkably rich theory has evolved around boosting, with connections to a range of topics including statistics, game theory, convex optimization, and information geometry. Boosting algorithms have also enjoyed practical success in such fields as biology, vision, and speech processing. At various times in its history, boosting has been perceived as mysterious, controversial, even paradoxical. This book, written by the inventors of the method, brings together, organizes, simplifies, and substantially extends two decades of research on boosting, presenting both theory and applications in a way that is accessible to readers from diverse backgrounds while also providing an authoritative reference for advanced researchers. With its introductory treatment of all material and its inclusion of exercises in every chapter, the book is appropriate for course use as well. --"@en ;
    schema:exampleOfWork <http://worldcat.org/entity/work/id/1032229637> ;
    schema:genre "Electronic books"@en ;
    schema:inLanguage "en" ;
    schema:isPartOf <http://experiment.worldcat.org/entity/work/data/1032229637#Series/adaptive_computation_and_machine_learning> ; # Adaptive computation and machine learning.
    schema:isSimilarTo <http://www.worldcat.org/oclc/758388404> ;
    schema:name "Boosting foundations and algorithms"@en ;
    schema:numberOfPages "526" ;
    schema:productID "794669892" ;
    schema:publication <http://www.worldcat.org/title/-/oclc/794669892#PublicationEvent/cambridge_ma_mit_press_c2012> ;
    schema:publisher <http://experiment.worldcat.org/entity/work/data/1032229637#Agent/mit_press> ; # MIT Press
    schema:url <http://search.ebscohost.com/login.aspx?direct=true&scope=site&db=nlebk&db=nlabk&AN=458478> ;
    schema:url <http://ieeexplore.ieee.org/xpl/bkabstractplus.jsp?bkn=6267536> ;
    schema:url <http://mitpress.mit.edu/images/products/books/9780262017183-f30.jpg> ;
    schema:url <http://www.books24x7.com/marc.asp?bookid=73652> ;
    schema:url <http://site.ebrary.com/lib/alltitles/Doc?id=10569012> ;
    schema:url <http://www.myilibrary.com?id=365528> ;
    schema:url <http://site.ebrary.com/id/10569012> ;
    schema:workExample <http://worldcat.org/isbn/9780262301183> ;
    wdrs:describedby <http://www.worldcat.org/title/-/oclc/794669892> ;
    .


Related Entities

<http://experiment.worldcat.org/entity/work/data/1032229637#Series/adaptive_computation_and_machine_learning> # Adaptive computation and machine learning.
    a bgn:PublicationSeries ;
    schema:hasPart <http://www.worldcat.org/oclc/794669892> ; # Boosting foundations and algorithms
    schema:name "Adaptive computation and machine learning." ;
    schema:name "Adaptive computation and machine learning" ;
    .

<http://experiment.worldcat.org/entity/work/data/1032229637#Topic/computers_enterprise_applications_business_intelligence_tools> # COMPUTERS / Enterprise Applications / Business Intelligence Tools
    a schema:Intangible ;
    schema:name "COMPUTERS / Enterprise Applications / Business Intelligence Tools"@en ;
    .

<http://experiment.worldcat.org/entity/work/data/1032229637#Topic/computers_intelligence_ai_&_semantics> # COMPUTERS / Intelligence (AI) & Semantics
    a schema:Intangible ;
    schema:name "COMPUTERS / Intelligence (AI) & Semantics"@en ;
    .

<http://id.worldcat.org/fast/1139041> # Supervised learning (Machine learning)
    a schema:Intangible ;
    schema:name "Supervised learning (Machine learning)"@en ;
    .

<http://id.worldcat.org/fast/1893023> # Boosting (Algorithms)
    a schema:Intangible ;
    schema:name "Boosting (Algorithms)"@en ;
    .

<http://viaf.org/viaf/46940747> # Robert E. Schapire
    a schema:Person ;
    schema:familyName "Schapire" ;
    schema:givenName "Robert E." ;
    schema:name "Robert E. Schapire" ;
    .

<http://viaf.org/viaf/63543180> # Yoav Freund
    a schema:Person ;
    schema:familyName "Freund" ;
    schema:givenName "Yoav" ;
    schema:name "Yoav Freund" ;
    .

<http://worldcat.org/isbn/9780262301183>
    a schema:ProductModel ;
    schema:description "electronic bk." ;
    schema:isbn "0262301180" ;
    schema:isbn "9780262301183" ;
    .

<http://www.worldcat.org/oclc/758388404>
    a schema:CreativeWork ;
    rdfs:label "Boosting." ;
    schema:description "Print version:" ;
    schema:isSimilarTo <http://www.worldcat.org/oclc/794669892> ; # Boosting foundations and algorithms
    .


Content-negotiable representations

Chiudi finestra

Per favore entra in WorldCat 

Non hai un account? Puoi facilmente crearne uno gratuito.