1. Identity statement | |
Reference Type | Journal Article |
Site | mtc-m16b.sid.inpe.br |
Holder Code | isadg {BR SPINPE} ibi 8JMKD3MGPCW/3DT298S |
Identifier | 6qtX3pFwXQZGivnK2Y/NmDG3 |
Repository | sid.inpe.br/mtc-m17@80/2006/12.04.13.25 (restricted access) |
Last Update | 2007:06.28.13.14.15 (UTC) administrator |
Metadata Repository | sid.inpe.br/mtc-m17@80/2006/12.04.13.25.19 |
Metadata Last Update | 2018:06.05.03.33.55 (UTC) administrator |
Secondary Key | INPE-14762-PRE/9733 |
ISSN | 0169-023X |
Citation Key | SantanaFrRoCaViReCo:2007:StImMo |
Title | Strategies for improving the modeling and interpretability of Bayesian networks |
Year | 2007 |
Month | Oct. |
Access Date | 2024, May 13 |
Secondary Type | PRE PI |
Number of Files | 1 |
Size | 447 KiB |
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2. Context | |
Author | 1 Santana, Ádamo L. 2 Francês, Carlos R. 3 Rocha, Cláudio A. 4 Carvalho, Solon Venâncio de 5 Vijaykumar, Nandamudi Lankalapalli 6 Rego, Liviane P. 7 Costa, João C. |
Resume Identifier | 1 2 3 4 5 8JMKD3MGP5W/3C9JHTU |
Group | 1 2 3 4 LAC-INPE-MCT-BR 5 LAC-INPE-MCT-BR |
Affiliation | 1 UFPA 2 UFPA 3 Universidade da Amazônia 4 Instituto Nacional de Pesquisas Espaciais (INPE) 5 Instituto Nacional de Pesquisas Espaciais (INPE) 6 UFPA 7 UFPA |
Journal | Data and Knowledge Engineering |
Volume | 63 |
Number | 1 |
Pages | 91-107 |
History (UTC) | 2006-12-04 13:25:54 :: simone -> administrator :: 2007-04-03 01:32:35 :: administrator -> simone :: 2007-06-28 13:14:15 :: simone -> administrator :: 2012-11-24 01:39:25 :: administrator -> simone :: 2007 2013-02-20 15:19:52 :: simone -> administrator :: 2007 2018-06-05 03:33:55 :: administrator -> marciana :: 2007 |
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3. Content and structure | |
Is the master or a copy? | is the master |
Content Stage | completed |
Transferable | 1 |
Content Type | External Contribution |
Keywords | Knowledge discovery Markov chains Bayesian networks Multivariate regression |
Abstract | One of the main factors for the knowledge discovery success is related to the comprehensibility of the patterns discovered by applying data mining techniques. Amongst which we can point out the Bayesian networks as one of the most prominent when considering the easiness of knowledge interpretation achieved. Bayesian networks, however, present limitations and disadvantages regarding their use and applicability. This paper presents an extension for the improvement of Bayesian networks, treating aspects such as performance, as well as interpretability and use of their results; incorporating genetic algorithms in the model, multivariate regression for structure learning and temporal aspects using Markov chains. |
Area | COMP |
Arrangement | urlib.net > BDMCI > Fonds > Produção anterior à 2021 > LABAC > Strategies for improving... |
doc Directory Content | access |
source Directory Content | there are no files |
agreement Directory Content | there are no files |
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4. Conditions of access and use | |
Language | en |
Target File | strategies for improving.pdf |
User Group | administrator simone |
Visibility | shown |
Copy Holder | SID/SCD |
Archiving Policy | denypublisher denyfinaldraft24 |
Read Permission | deny from all and allow from 150.163 |
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5. Allied materials | |
Next Higher Units | 8JMKD3MGPCW/3ESGTTP |
Dissemination | PORTALCAPES |
Host Collection | lcp.inpe.br/ignes/2004/02.12.18.39 cptec.inpe.br/walmeida/2003/04.25.17.12 |
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6. Notes | |
Empty Fields | alternatejournal archivist callnumber copyright creatorhistory descriptionlevel documentstage doi e-mailaddress electronicmailaddress format isbn label lineage mark mirrorrepository nextedition notes orcid parameterlist parentrepositories previousedition previouslowerunit progress project readergroup rightsholder schedulinginformation secondarydate secondarymark session shorttitle sponsor subject tertiarymark tertiarytype typeofwork url versiontype |
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7. Description control | |
e-Mail (login) | marciana |
update | |
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