Approximation methods for efficient learning of Bayesian networks:
Saved in:
| Main Author: | |
|---|---|
| Format: | Thesis Electronic eBook |
| Language: | English |
| Published: |
Amsterdam
IOS Press
c2008
|
| Series: | Frontiers in artificial intelligence and applications
Frontiers in artificial intelligence and applications v. 168 |
| Subjects: | |
| Physical Description: | vii, 137 p. |
| ISBN: | 1586038214 9781586038212 |
Staff View
MARC
| LEADER | 00000nmm a2200000zcb4500 | ||
|---|---|---|---|
| 001 | BV044838394 | ||
| 003 | DE-604 | ||
| 005 | 20180305 | ||
| 007 | cr|uuu---uuuuu | ||
| 008 | 180305s2008 |||| o||u| ||||||eng d | ||
| 020 | |a 1586038214 |9 1-58603-821-4 | ||
| 020 | |a 9781586038212 |9 978-1-58603-821-2 | ||
| 035 | |a (ZDB-38-ESG)ebr10216841 | ||
| 035 | |a (OCoLC)608622263 | ||
| 035 | |a (DE-599)BVBBV044838394 | ||
| 040 | |a DE-604 |b ger |e aacr | ||
| 041 | 0 | |a eng | |
| 100 | 1 | |a Riggelsen, Carsten |e Verfasser |4 aut | |
| 245 | 1 | 0 | |a Approximation methods for efficient learning of Bayesian networks |c Carsten Riggelsen |
| 264 | 1 | |a Amsterdam |b IOS Press |c c2008 | |
| 300 | |a vii, 137 p. | ||
| 336 | |b txt |2 rdacontent | ||
| 337 | |b c |2 rdamedia | ||
| 338 | |b cr |2 rdacarrier | ||
| 490 | 0 | |a Frontiers in artificial intelligence and applications | |
| 490 | 0 | |a Frontiers in artificial intelligence and applications |v v. 168 | |
| 502 | |a Thesis (Ph.D.)--Utrecht University, 2006 | ||
| 505 | 8 | |a Includes bibliographical references (p. [133]-137) | |
| 650 | 4 | |a Bayesian statistical decision theory | |
| 650 | 4 | |a Machine learning | |
| 650 | 4 | |a Neural networks (Computer science) | |
| 655 | 7 | |8 1\p |0 (DE-588)4113937-9 |a Hochschulschrift |2 gnd-content | |
| 912 | |a ZDB-38-ESG | ||
| 999 | |a oai:aleph.bib-bvb.de:BVB01-030233256 | ||
| 883 | 1 | |8 1\p |a cgwrk |d 20201028 |q DE-101 |u https://d-nb.info/provenance/plan#cgwrk | |
Record in the Search Index
| _version_ | 1804178344946696192 |
|---|---|
| any_adam_object | |
| author | Riggelsen, Carsten |
| author_facet | Riggelsen, Carsten |
| author_role | aut |
| author_sort | Riggelsen, Carsten |
| author_variant | c r cr |
| building | Verbundindex |
| bvnumber | BV044838394 |
| collection | ZDB-38-ESG |
| contents | Includes bibliographical references (p. [133]-137) |
| ctrlnum | (ZDB-38-ESG)ebr10216841 (OCoLC)608622263 (DE-599)BVBBV044838394 |
| format | Thesis Electronic eBook |
| fullrecord | <?xml version="1.0" encoding="UTF-8"?><collection xmlns="http://www.loc.gov/MARC21/slim"><record><leader>01395nmm a2200385zcb4500</leader><controlfield tag="001">BV044838394</controlfield><controlfield tag="003">DE-604</controlfield><controlfield tag="005">20180305 </controlfield><controlfield tag="007">cr|uuu---uuuuu</controlfield><controlfield tag="008">180305s2008 |||| o||u| ||||||eng d</controlfield><datafield tag="020" ind1=" " ind2=" "><subfield code="a">1586038214</subfield><subfield code="9">1-58603-821-4</subfield></datafield><datafield tag="020" ind1=" " ind2=" "><subfield code="a">9781586038212</subfield><subfield code="9">978-1-58603-821-2</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(ZDB-38-ESG)ebr10216841</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(OCoLC)608622263</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-599)BVBBV044838394</subfield></datafield><datafield tag="040" ind1=" " ind2=" "><subfield code="a">DE-604</subfield><subfield code="b">ger</subfield><subfield code="e">aacr</subfield></datafield><datafield tag="041" ind1="0" ind2=" "><subfield code="a">eng</subfield></datafield><datafield tag="100" ind1="1" ind2=" "><subfield code="a">Riggelsen, Carsten</subfield><subfield code="e">Verfasser</subfield><subfield code="4">aut</subfield></datafield><datafield tag="245" ind1="1" ind2="0"><subfield code="a">Approximation methods for efficient learning of Bayesian networks</subfield><subfield code="c">Carsten Riggelsen</subfield></datafield><datafield tag="264" ind1=" " ind2="1"><subfield code="a">Amsterdam</subfield><subfield code="b">IOS Press</subfield><subfield code="c">c2008</subfield></datafield><datafield tag="300" ind1=" " ind2=" "><subfield code="a">vii, 137 p.</subfield></datafield><datafield tag="336" ind1=" " ind2=" "><subfield code="b">txt</subfield><subfield code="2">rdacontent</subfield></datafield><datafield tag="337" ind1=" " ind2=" "><subfield code="b">c</subfield><subfield code="2">rdamedia</subfield></datafield><datafield tag="338" ind1=" " ind2=" "><subfield code="b">cr</subfield><subfield code="2">rdacarrier</subfield></datafield><datafield tag="490" ind1="0" ind2=" "><subfield code="a">Frontiers in artificial intelligence and applications</subfield></datafield><datafield tag="490" ind1="0" ind2=" "><subfield code="a">Frontiers in artificial intelligence and applications</subfield><subfield code="v">v. 168</subfield></datafield><datafield tag="502" ind1=" " ind2=" "><subfield code="a">Thesis (Ph.D.)--Utrecht University, 2006</subfield></datafield><datafield tag="505" ind1="8" ind2=" "><subfield code="a">Includes bibliographical references (p. [133]-137)</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Bayesian statistical decision theory</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Machine learning</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Neural networks (Computer science)</subfield></datafield><datafield tag="655" ind1=" " ind2="7"><subfield code="8">1\p</subfield><subfield code="0">(DE-588)4113937-9</subfield><subfield code="a">Hochschulschrift</subfield><subfield code="2">gnd-content</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">ZDB-38-ESG</subfield></datafield><datafield tag="999" ind1=" " ind2=" "><subfield code="a">oai:aleph.bib-bvb.de:BVB01-030233256</subfield></datafield><datafield tag="883" ind1="1" ind2=" "><subfield code="8">1\p</subfield><subfield code="a">cgwrk</subfield><subfield code="d">20201028</subfield><subfield code="q">DE-101</subfield><subfield code="u">https://d-nb.info/provenance/plan#cgwrk</subfield></datafield></record></collection> |
| genre | 1\p (DE-588)4113937-9 Hochschulschrift gnd-content |
| genre_facet | Hochschulschrift |
| id | DE-604.BV044838394 |
| illustrated | Not Illustrated |
| indexdate | 2024-07-10T08:02:29Z |
| institution | BVB |
| isbn | 1586038214 9781586038212 |
| language | English |
| oai_aleph_id | oai:aleph.bib-bvb.de:BVB01-030233256 |
| oclc_num | 608622263 |
| open_access_boolean | |
| physical | vii, 137 p. |
| psigel | ZDB-38-ESG |
| publishDate | 2008 |
| publishDateSearch | 2008 |
| publishDateSort | 2008 |
| publisher | IOS Press |
| record_format | marc |
| series2 | Frontiers in artificial intelligence and applications |
| spelling | Riggelsen, Carsten Verfasser aut Approximation methods for efficient learning of Bayesian networks Carsten Riggelsen Amsterdam IOS Press c2008 vii, 137 p. txt rdacontent c rdamedia cr rdacarrier Frontiers in artificial intelligence and applications Frontiers in artificial intelligence and applications v. 168 Thesis (Ph.D.)--Utrecht University, 2006 Includes bibliographical references (p. [133]-137) Bayesian statistical decision theory Machine learning Neural networks (Computer science) 1\p (DE-588)4113937-9 Hochschulschrift gnd-content 1\p cgwrk 20201028 DE-101 https://d-nb.info/provenance/plan#cgwrk |
| spellingShingle | Riggelsen, Carsten Approximation methods for efficient learning of Bayesian networks Includes bibliographical references (p. [133]-137) Bayesian statistical decision theory Machine learning Neural networks (Computer science) |
| subject_GND | (DE-588)4113937-9 |
| title | Approximation methods for efficient learning of Bayesian networks |
| title_auth | Approximation methods for efficient learning of Bayesian networks |
| title_exact_search | Approximation methods for efficient learning of Bayesian networks |
| title_full | Approximation methods for efficient learning of Bayesian networks Carsten Riggelsen |
| title_fullStr | Approximation methods for efficient learning of Bayesian networks Carsten Riggelsen |
| title_full_unstemmed | Approximation methods for efficient learning of Bayesian networks Carsten Riggelsen |
| title_short | Approximation methods for efficient learning of Bayesian networks |
| title_sort | approximation methods for efficient learning of bayesian networks |
| topic | Bayesian statistical decision theory Machine learning Neural networks (Computer science) |
| topic_facet | Bayesian statistical decision theory Machine learning Neural networks (Computer science) Hochschulschrift |
| work_keys_str_mv | AT riggelsencarsten approximationmethodsforefficientlearningofbayesiannetworks |