skip to content
<>. Preview this item
ClosePreview this item
Checking...

Dataset shift in machine learning /

Author: [edited by] Joaquin Qui�nonero-Candela [and others]. Qui�nonero-Candela, Joaquin. ;
Publisher: Cambridge, Mass. : MIT Press, ©2009.
Series: Neural information processing series.
Edition/Format:   eBook : Document : EnglishView all editions and formats
Summary:
This work is an overview of recent efforts in the machine learning community to deal with dataset and covariate shift which occurs when test and training inputs and outputs have different distributions.
Rating:

(not yet rated) 0 with reviews - Be the first.

Subjects
More like this

Find a copy online

Find a copy in the library

&AllPage.SpinnerRetrieving; Finding libraries that hold this item...

Details

Genre/Form: Electronic books
Additional Physical Format: Print version:
<>.
Cambridge, Mass. : MIT Press, ©2009
(DLC) 2008020394
(OCoLC)227205909
Material Type: Document, Internet resource
Document Type: Internet Resource, Computer File
All Authors / Contributors: [edited by] Joaquin Qui�nonero-Candela [and others]. Qui�nonero-Candela, Joaquin. ;
ISBN: 9780262255103 0262255103
OCLC Number: 992069424
Description: 1 online resource (xv, 229 pages) : illustrations.
Contents: Series Foreword; Preface; I --
Introduction to Dataset Shift; 1 --
When Training and Test Sets Are Different: Characterizing Learning Transfer; 2 --
Projection and Projectability; II --
Theoretical Views on Dataset and Covariate Shift; 3 --
Binary Classi cation under Sample Selection Bias; 4 --
On Bayesian Transduction: Implications for the Covariate Shift Problem; 5 --
On the Training/Test Distributions Gap: A Data Representation Learning Framework; III --
Algorithms for Covariate Shift; 6 --
Geometry of Covariate Shift with Applications to Active Learning 7 --
A Conditional Expectation Approach to Model Selection and Active Learning under Covariate Shift 8 --
Covariate Shift by Kernel Mean Matching; 9 --
Discriminative Learning under Covariate Shift with a Single Optimization Problem; 10 --
An Adversarial View of Covariate Shift and a Minimax Approach; IV --
Discussion; 11 --
Author Comments; References; Notation and Symbols; Contributors; Index
Series Title: Neural information processing series.

Abstract:

This work is an overview of recent efforts in the machine learning community to deal with dataset and covariate shift which occurs when test and training inputs and outputs have different distributions.

Reviews

User-contributed reviews
Retrieving GoodReads reviews...
Retrieving DOGObooks reviews...

Tags

Be the first.

Similar Items

Related Subjects:(1)

Confirm this request

You may have already requested this item. Please select Ok if you would like to proceed with this request anyway.

Linked Data


\n\n

Primary Entity<\/h3>\n
<http:\/\/www.worldcat.org\/oclc\/992069424<\/a>> # Dataset shift in machine learning<\/span>\n\u00A0\u00A0\u00A0\u00A0a \nschema:MediaObject<\/a>, schema:Book<\/a>, schema:CreativeWork<\/a> ;\u00A0\u00A0\u00A0\nlibrary:oclcnum<\/a> \"992069424<\/span>\" ;\u00A0\u00A0\u00A0\nlibrary:placeOfPublication<\/a> <http:\/\/experiment.worldcat.org\/entity\/work\/data\/136959600#Place\/cambridge_mass<\/a>> ; # Cambridge, Mass.<\/span>\n\u00A0\u00A0\u00A0\nlibrary:placeOfPublication<\/a> <http:\/\/id.loc.gov\/vocabulary\/countries\/mau<\/a>> ;\u00A0\u00A0\u00A0\nschema:about<\/a> <http:\/\/dewey.info\/class\/006.31\/e22\/<\/a>> ;\u00A0\u00A0\u00A0\nschema:about<\/a> <http:\/\/experiment.worldcat.org\/entity\/work\/data\/136959600#Topic\/machine_learning<\/a>> ; # Machine learning<\/span>\n\u00A0\u00A0\u00A0\nschema:bookFormat<\/a> schema:EBook<\/a> ;\u00A0\u00A0\u00A0\nschema:copyrightYear<\/a> \"2009<\/span>\" ;\u00A0\u00A0\u00A0\nschema:datePublished<\/a> \"2009<\/span>\" ;\u00A0\u00A0\u00A0\nschema:description<\/a> \"This work is an overview of recent efforts in the machine learning community to deal with dataset and covariate shift which occurs when test and training inputs and outputs have different distributions.<\/span>\"@en<\/a> ;\u00A0\u00A0\u00A0\nschema:description<\/a> \"Series Foreword; Preface; I -- Introduction to Dataset Shift; 1 -- When Training and Test Sets Are Different: Characterizing Learning Transfer; 2 -- Projection and Projectability; II -- Theoretical Views on Dataset and Covariate Shift; 3 -- Binary Classi cation under Sample Selection Bias; 4 -- On Bayesian Transduction: Implications for the Covariate Shift Problem; 5 -- On the Training\/Test Distributions Gap: A Data Representation Learning Framework; III -- Algorithms for Covariate Shift; 6 -- Geometry of Covariate Shift with Applications to Active Learning<\/span>\"@en<\/a> ;\u00A0\u00A0\u00A0\nschema:exampleOfWork<\/a> <http:\/\/worldcat.org\/entity\/work\/id\/136959600<\/a>> ;\u00A0\u00A0\u00A0\nschema:genre<\/a> \"Electronic books<\/span>\"@en<\/a> ;\u00A0\u00A0\u00A0\nschema:inLanguage<\/a> \"en<\/span>\" ;\u00A0\u00A0\u00A0\nschema:isPartOf<\/a> <http:\/\/experiment.worldcat.org\/entity\/work\/data\/136959600#Series\/neural_information_processing_series<\/a>> ; # Neural information processing series.<\/span>\n\u00A0\u00A0\u00A0\nschema:isSimilarTo<\/a> <http:\/\/www.worldcat.org\/oclc\/227205909<\/a>> ;\u00A0\u00A0\u00A0\nschema:name<\/a> \"Dataset shift in machine learning<\/span>\"@en<\/a> ;\u00A0\u00A0\u00A0\nschema:productID<\/a> \"992069424<\/span>\" ;\u00A0\u00A0\u00A0\nschema:publication<\/a> <http:\/\/www.worldcat.org\/title\/-\/oclc\/992069424#PublicationEvent\/cambridge_mass_mit_press_2009<\/a>> ;\u00A0\u00A0\u00A0\nschema:publisher<\/a> <http:\/\/experiment.worldcat.org\/entity\/work\/data\/136959600#Agent\/mit_press<\/a>> ; # MIT Press<\/span>\n\u00A0\u00A0\u00A0\nschema:url<\/a> <http:\/\/search.ebscohost.com\/login.aspx?direct=true&scope=site&db=nlebk&db=nlabk&AN=259275<\/a>> ;\u00A0\u00A0\u00A0\nschema:url<\/a> <http:\/\/public.ebookcentral.proquest.com\/choice\/publicfullrecord.aspx?p=3338975<\/a>> ;\u00A0\u00A0\u00A0\nschema:url<\/a> <http:\/\/site.ebrary.com\/id\/10269466<\/a>> ;\u00A0\u00A0\u00A0\nschema:workExample<\/a> <http:\/\/worldcat.org\/isbn\/9780262255103<\/a>> ;\u00A0\u00A0\u00A0\nwdrs:describedby<\/a> <http:\/\/www.worldcat.org\/title\/-\/oclc\/992069424<\/a>> ;\u00A0\u00A0\u00A0\u00A0.\n\n\n<\/div>\n\n

Related Entities<\/h3>\n
<http:\/\/dewey.info\/class\/006.31\/e22\/<\/a>>\u00A0\u00A0\u00A0\u00A0a \nschema:Intangible<\/a> ;\u00A0\u00A0\u00A0\u00A0.\n\n\n<\/div>\n
<http:\/\/experiment.worldcat.org\/entity\/work\/data\/136959600#Agent\/mit_press<\/a>> # MIT Press<\/span>\n\u00A0\u00A0\u00A0\u00A0a \nbgn:Agent<\/a> ;\u00A0\u00A0\u00A0\nschema:name<\/a> \"MIT Press<\/span>\" ;\u00A0\u00A0\u00A0\u00A0.\n\n\n<\/div>\n
<http:\/\/experiment.worldcat.org\/entity\/work\/data\/136959600#Place\/cambridge_mass<\/a>> # Cambridge, Mass.<\/span>\n\u00A0\u00A0\u00A0\u00A0a \nschema:Place<\/a> ;\u00A0\u00A0\u00A0\nschema:name<\/a> \"Cambridge, Mass.<\/span>\" ;\u00A0\u00A0\u00A0\u00A0.\n\n\n<\/div>\n
<http:\/\/experiment.worldcat.org\/entity\/work\/data\/136959600#Series\/neural_information_processing_series<\/a>> # Neural information processing series.<\/span>\n\u00A0\u00A0\u00A0\u00A0a \nbgn:PublicationSeries<\/a> ;\u00A0\u00A0\u00A0\nschema:hasPart<\/a> <http:\/\/www.worldcat.org\/oclc\/992069424<\/a>> ; # Dataset shift in machine learning<\/span>\n\u00A0\u00A0\u00A0\nschema:name<\/a> \"Neural information processing series.<\/span>\" ;\u00A0\u00A0\u00A0\nschema:name<\/a> \"Neural information processing series<\/span>\" ;\u00A0\u00A0\u00A0\u00A0.\n\n\n<\/div>\n
<http:\/\/experiment.worldcat.org\/entity\/work\/data\/136959600#Topic\/machine_learning<\/a>> # Machine learning<\/span>\n\u00A0\u00A0\u00A0\u00A0a \nschema:Intangible<\/a> ;\u00A0\u00A0\u00A0\nschema:name<\/a> \"Machine learning<\/span>\"@en<\/a> ;\u00A0\u00A0\u00A0\u00A0.\n\n\n<\/div>\n
<http:\/\/id.loc.gov\/vocabulary\/countries\/mau<\/a>>\u00A0\u00A0\u00A0\u00A0a \nschema:Place<\/a> ;\u00A0\u00A0\u00A0\ndcterms:identifier<\/a> \"mau<\/span>\" ;\u00A0\u00A0\u00A0\u00A0.\n\n\n<\/div>\n
<http:\/\/worldcat.org\/isbn\/9780262255103<\/a>>\u00A0\u00A0\u00A0\u00A0a \nschema:ProductModel<\/a> ;\u00A0\u00A0\u00A0\nschema:isbn<\/a> \"0262255103<\/span>\" ;\u00A0\u00A0\u00A0\nschema:isbn<\/a> \"9780262255103<\/span>\" ;\u00A0\u00A0\u00A0\u00A0.\n\n\n<\/div>\n
<http:\/\/www.worldcat.org\/oclc\/227205909<\/a>>\u00A0\u00A0\u00A0\u00A0a \nschema:CreativeWork<\/a> ;\u00A0\u00A0\u00A0\nrdfs:label<\/a> \"<>.<\/span>\" ;\u00A0\u00A0\u00A0\nschema:description<\/a> \"Print version:<\/span>\" ;\u00A0\u00A0\u00A0\nschema:isSimilarTo<\/a> <http:\/\/www.worldcat.org\/oclc\/992069424<\/a>> ; # Dataset shift in machine learning<\/span>\n\u00A0\u00A0\u00A0\u00A0.\n\n\n<\/div>\n
<http:\/\/www.worldcat.org\/title\/-\/oclc\/992069424<\/a>>\u00A0\u00A0\u00A0\u00A0a \ngenont:InformationResource<\/a>, genont:ContentTypeGenericResource<\/a> ;\u00A0\u00A0\u00A0\nschema:about<\/a> <http:\/\/www.worldcat.org\/oclc\/992069424<\/a>> ; # Dataset shift in machine learning<\/span>\n\u00A0\u00A0\u00A0\nschema:dateModified<\/a> \"2019-07-18<\/span>\" ;\u00A0\u00A0\u00A0\nvoid:inDataset<\/a> <http:\/\/purl.oclc.org\/dataset\/WorldCat<\/a>> ;\u00A0\u00A0\u00A0\u00A0.\n\n\n<\/div>\n