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23 TRIPLES      18 PREDICATES      24 URIs      13 LITERALS

Subject Predicate Object
1 book-editions:8858000580e7f5f2d17e912489ba95a6 sg:bookType Monograph
2 sg:chapterCount 11
3 sg:copyrightHolder Springer Science+Business Media, LLC
4 sg:copyrightYear 2012
5 sg:ddsId 168428
6 sg:description <p>Covers all existing methods developed for ensemble learning</p><p>Presents overview and in-depth knowledge about ensemble learning</p><p>Discusses the pros and cons of various ensemble learning methods</p><p>Demonstrate how ensemble learning can be used with real world applications</p>
7 sg:editionNumber 1
8 sg:hasContributingOrganization grid-institutes:grid.419815.0
9 grid-institutes:grid.420747.2
10 sg:hasContribution contributions:c355eb10fa578bd3fef7cc5c2e46852a
11 contributions:d296633beef3a46e986643d870d77bb6
12 sg:hasProductMarketCode product-market-codes:I00001
13 product-market-codes:I18030
14 product-market-codes:T
15 product-market-codes:T11014
16 sg:language En
17 sg:license
18 sg:publisher Springer US
19 sg:scigraphId 8858000580e7f5f2d17e912489ba95a6
20 sg:subtitle Methods and Applications
21 sg:title Ensemble Machine Learning
22 rdf:type sg:BookEdition
23 rdfs:label BookEdition: Ensemble Machine Learning

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