vti_encoding:SR|utf8-nl vti_author:SR|Slim-PC\\SlimSly vti_modifiedby:SR|Slim-PC\\SlimSly vti_timelastmodified:TR|15 Jul 2013 12:14:57 -0000 vti_timecreated:TR|15 Jul 2013 12:05:20 -0000 vti_title:SR|Overview of Bayesian Network vti_extenderversion:SR|12.0.0.0 vti_backlinkinfo:VX| vti_nexttolasttimemodified:TW|15 Jul 2013 12:14:27 -0000 vti_cacheddtm:TX|15 Jul 2013 12:14:57 -0000 vti_filesize:IR|10138 vti_cachedtitle:SR|Overview of Bayesian Network vti_cachedbodystyle:SR| vti_cachedlinkinfo:VX|H|favicon.ico Q|default.css Q|headerpicture.css S|images/sjp_logo.jpg A|search.php H|http://www.sjpub.org H|http://www.sjpub.org/journals.html H|http://www.sjpub.org/sjms.html H|http://www.sjpub.org/submit.html H|http://www.sjpub.org/sjeeditorial.html H|http://www.sjpub.org/aboutus.html H|http://www.sjpub.org/contactus.html H|http://creativecommons.org/licenses/by/3.0/ H|http://www.sjpub.org/sjms/sjms-105.pdf H|http://www.sjpub.org/sjms.html D|clsid:D27CDB6E-AE6D-11cf-96B8-444553540000 D|http://fpdownload.macromedia.com/pub/shockwave/cabs/flash/swflash.cab S|Journal-Cover.swf S|Journal-Cover.swf H|http://www.sjpub.org/sje-index.html H|http://www.sjpub.org/sje-bibliographic.html H|http://www.sjpub.org/sjms-aim.html H|http://www.sjpub.org/sjms.html H|http://www.sjpub.org/sjmseditorial.html H|http://www.sjpub.org/contactus.html H|http://www.sjpub.org/publishwithus.html H|http://www.sjpub.org/authorguide.html H|http://www.sjpub.org/submit.html H|http://www.sjpub.org/authorfaq.html H|http://www.sjpub.org/joineditors.html H|http://www.sjpub.org/joinreviewers.html H|http://www.sjpub.org/sitemap.html vti_cachedsvcrellinks:VX|NHUS|sjms/abstract/favicon.ico FQUS|sjms/abstract/default.css FQUS|sjms/abstract/headerpicture.css FSUS|sjms/abstract/images/sjp_logo.jpg NAUS|sjms/abstract/search.php NHHS|http://www.sjpub.org NHHS|http://www.sjpub.org/journals.html NHHS|http://www.sjpub.org/sjms.html NHHS|http://www.sjpub.org/submit.html NHHS|http://www.sjpub.org/sjeeditorial.html NHHS|http://www.sjpub.org/aboutus.html NHHS|http://www.sjpub.org/contactus.html NHHS|http://creativecommons.org/licenses/by/3.0/ NHHS|http://www.sjpub.org/sjms/sjms-105.pdf NHHS|http://www.sjpub.org/sjms.html NDUS|clsid:D27CDB6E-AE6D-11cf-96B8-444553540000 NDHS|http://fpdownload.macromedia.com/pub/shockwave/cabs/flash/swflash.cab FSUS|sjms/abstract/Journal-Cover.swf FSUS|sjms/abstract/Journal-Cover.swf NHHS|http://www.sjpub.org/sje-index.html NHHS|http://www.sjpub.org/sje-bibliographic.html NHHS|http://www.sjpub.org/sjms-aim.html NHHS|http://www.sjpub.org/sjms.html NHHS|http://www.sjpub.org/sjmseditorial.html NHHS|http://www.sjpub.org/contactus.html NHHS|http://www.sjpub.org/publishwithus.html NHHS|http://www.sjpub.org/authorguide.html NHHS|http://www.sjpub.org/submit.html NHHS|http://www.sjpub.org/authorfaq.html NHHS|http://www.sjpub.org/joineditors.html NHHS|http://www.sjpub.org/joinreviewers.html NHHS|http://www.sjpub.org/sitemap.html vti_cachedneedsrewrite:BR|false vti_cachedhasbots:BR|false vti_cachedhastheme:BR|false vti_cachedhasborder:BR|false vti_metatags:VR|HTTP-EQUIV=Content-Type text/html;\\ charset=iso-8859-1 citation_author Loc\\ Nguyen citation_title Overview\\ of\\ Bayesian\\ Network citation_pdf_url http://www.sjpub.org/sjms/sjms-105.pdf citation_year 2013 citation_online_date 2013 citation_journal_title Science\\ Journal\\ of\\ Mathematics\\ and\\ Statistics citation_abstract Bayesian\\ network\\ is\\ applied\\ widely\\ in\\ machine\\ learning,\\ data\\ mining,\r\ndiagnosis,\\ etc;\\ it\\ has\\ a\\ solid\\ evidence-based\\ inference\\ which\\ is\\ familiar\\ to\r\nhuman\\ intuition.\\ However\\ Bayesian\\ network\\ causes\\ a\\ little\\ confusion\r\nbecause\\ there\\ are\\ many\\ complicated\\ concepts,\\ formulas\\ and\\ diagrams\r\nrelating\\ to\\ it.\\ Such\\ concepts\\ should\\ be\\ organized\\ and\\ presented\\ in\\ clear\r\nmanner\\ so\\ as\\ to\\ be\\ easy\\ to\\ understand\\ it.\\ This\\ is\\ the\\ goal\\ of\\ this\\ report.\r\nThis\\ report\\ includes\\ 4\\ main\\ parts\\ that\\ cover\\ principles\\ of\\ Bayesian\r\nnetwork:\r\nPart\\ 1:\\ Introduction\\ to\\ Bayesian\\ network\\ giving\\ some\\ basic\\ concepts.\r\nPart\\ 2:\\ Bayesian\\ network\\ inference\\ discussing\\ inference\\ mechanism\\ inside\r\nBayesian\\ network.\r\nPart\\ 3:\\ Parameter\\ learning\\ tells\\ us\\ how\\ to\\ update\\ parameters\\ of\\ Bayesian\r\nnetwork.\r\nPart\\ 4:\\ Structure\\ learning\\ surveys\\ some\\ main\\ techniques\\ to\\ build\\ up\r\nBayesian\\ network. dc.rights http://creativecommons.org/licenses/by/3.0/ citation_volume 2013 citation_publisher Science\\ Journal\\ Publication citation_issn 2276-6324 citation_abstract_html_url http://www.sjpub.org/sjms/abstract/sjms-105.html vti_charset:SR|iso-8859-1