text_combined: ohwwlejspbfotbplistscmswaikatoacnz send wekalist mailing list submissions iuxxdkqklistscmswaikatoacnz subscribe unsubscribe via world wide web visit httpslistscmswaikatoacnzmailmanlistinfowekalist via email send message subject body help ohwwlejspbfotbplistscmswaikatoacnz reach person managing list pobypuhshvhzjlistscmswaikatoacnz replying please edit subject line specific contents wekalist digest todays topics 1 classifier choose hesuoju 2 classifier choose bernhard pfahringer 3 cobweb clustering mark hall 4 2 step calssifications 5 weka lda dragi kocev 6 weka2uml michael 7 weka running slow windows vista carmelo saffioti 8 weka running slow windows vista marco genova fjlxnwshotmailcom sat apr 26 154931 2008 message 1 date sun 2 mar 2008 180002 0800 hesuoju subject wekalist classifier choose wekalist messageid contenttype textplain charsetgb2312 hi luc pretty hard help described neither datasets kind attributes many attributes many instances training validation datasets possibly separated original dataset etc goals du want test explanation hypotheses looking robustness training validation datasets possibly separated original dataset try train learner training instance see learner working ok testing instance want test explanation hypotheses yes actually working research paper classification thanks great help suoju plqebtmylhuiyuzyplgmailcom sat apr 26 154931 2008 message 2 date sun 2 mar 2008 232239 1300 bernhard pfahringer subject wekalist classifier choose weka machine learning workbench list messageid 17b0dx2u0333872317b07920w33fizm3f7b07xm00xj3mailgmailcom contenttype textplain charsetiso88591 hi data likely violates important assumption samples supposed drawn iid underlying distribution case crossvalidation results provide meaningful predictions future performance bernhard 3208 hesuoju wrote hi luc thank much reply training data 60 instance following 3 class group b c relation data attribute food numeric attribute powerup numeric attribute killghost numeric attribute fruit numeric attribute dis_1 numeric attribute dis_2 numeric attribute dis_3 numeric attribute dis_4 numeric attribute time numeric attribute score numeric attribute result numeric attribute type abc data 1773206275928265994070325200a 2384315875875926815351641300a 69000488512556664136886900a 2033006844995537424220321800a 1713106166396476263689120600a 951005795936585972146910000a 1933106726957967704571922800a 1001007435046336152523510500a 2424008328286178594834326201a 1001115525876578022551620000a 1001007228168217991967210500a 2424208107018048435042230201a 1833105996586776983714121800a 2424106715075916994606328201a 1172107945166095932379614700a 1753206166747016563568725000a 2424017238898028134659433701a 1933015907416836873870328300a 1202006987095566952312513000a 1462216446757637022906229100a 3600052364666566277033600b 752604724834844752934344500b 1934605745284824694934337300b 861105646986666351545311100b 1433715465095004774132849300b 1263604315125014744529732100b 1814715105045314924993851600b 671204394455285371586013200b 13441004625314374335765755400b 2084815674404866536400054300b 1213604504494765873593831600b 531203915274865121550011800b 1673605355765715484354752200b 622504024765224651989127200b 14441113484895664525245383900b 20741114764614984647707986200b 22041114904795456076657891500b 961204575877077571957816100b 1373706074434774833743745200b 721204514545524751559413700b 1573714524835226024656368700c 1282515315935275516296941300c 1302615365735945743682957500c 19931014855845545555693786900c 81000424513429523151258100c 24241204915524955639406390201c 50000501611682725107975000c 1932615194926075345861055800c 54000382563576605128135400c 741204485164726212311013900c 1562715845865755955481268100c 18231014985294885566232993200c 2183716164996396237593860800c 2424814665075815118123467701c 2323815404535215119056266200c 2243715924684717215761057400c 2424915265326724959143869701c 2022415605386515267376544700c 2233716185287255596893857300c 24241114935625007008685981701c testing data following 20 instance class relation datatest attribute food numeric attribute powerup numeric attribute killghost numeric attribute fruit numeric attribute dis_1 numeric attribute dis_2 numeric attribute dis_3 numeric attribute dis_4 numeric attribute time numeric attribute score numeric attribute result numeric attribute type abc data 2404105915716887235203128000a 2204206716236425265031328000a 47000396471560544107814700a 2293106616116776164734426400a 2424107595986276255020328201a 1622305486535795853462525200a 2424017787425946585178133701a 1572105845017077282951518700a 2224504265445656324987544200a 1021005795895104822192210700a 43000395442407367124684300a 40000315388349331102504000a 66000420496436333144076600a 1110003355415354092039011100a 1700034839840240449371700a 1012007567476254782631311100a 1171005844594455412312512200a 1600029923221921949061600a 1200005145714814872100012000a 4800038944338338897034800a question use diff bayesian analyse data naivebayesian bayesiannet method 80 correct training data 40 correct testing data completenaivebayesian method got 60 correct training data 95 correct testing data one classifier choose thanks suoju _______________________________________________ wekalist mailing list iuxxdkqklistscmswaikatoacnz httpslistscmswaikatoacnzmailmanlistinfowekalist bernhard pfahringer dept computer science university waikato httpwwwcswaikatoacnzbernhard 64 7 838 4041 vafzspentahoorg sat apr 26 154931 2008 message 3 date mon 3 mar 2008 091916 1300 mark hall subject wekalist cobweb clustering weka machine learning workbench list messageid 20080302201915ga16536cygnuslocal contenttype textplain charsetusascii thu feb 28 2008 084114pm 0500 priyanka sharma wrote nominal attribute attribute value also certain confidence associated eg nominal attribute values high low also confidence 08 02 wondering kind data structure could use problem thinking string double represent two values pretty shaky attribute already stores values fastvector would add data structure holding confidence values cheers mark mark hall senior developerconsultant pentaho open source business intelligence citadel international suite 340 5950 hazeltine national dr orlando fl 32822 usa 64 7 8473537 office 64 21 399132 mobile 1 815 5508637 fax skype markandrewhall yahoo mark_andrew_hall download latest release today gkzijpbcifdmecssciteckobeuacjp sat apr 26 154931 2008 message 4 date mon 03 mar 2008 171747 0900 katsuyuki tanaka subject wekalist 2 step calssifications iuxxdkqklistscmswaikatoacnz messageid 47cbb42b2040605mecssciteckobeuacjp contenttype textplain charsetiso2022jp hi wondering anyone could help following problem would like would like perform 2steps classification one data class attirbute tf 1st classification want caputure predicted result tf categoryresults maybe 10cv using test data according predicted data want perform another calssification classify like cat14 evaluate method im trouble getting predicted data java code also know print predicted data gui dont know extract predicted data pointing data arff file feel itll troublesome manually even know correspond predicted data arff file easy way thisim assuming using classifier 1st 2nd classifications regrads katsu yeinurupkngmailcom sat apr 26 154931 2008 message 5 date tue 4 mar 2008 110626 0100 dragi kocev subject wekalist weka lda iuxxdkqklistscmswaikatoacnz messageid contenttype textplain charsetiso88591 hi need analyze datasets using linear discriminant analysis lda wondering someone implemented weka implementation lda discussed wekalist years regards dragi next part html attachment scrubbed url httpslistscmswaikatoacnzpipermailwekalistattachments200803043be1977aattachment0001html vdsvugsohucom sat apr 26 154931 2008 message 6 date tue 4 mar 2008 180723 0800 michael subject wekalist weka2uml iuxxdkqklistscmswaikatoacnz messageid give uml weka tks lot yruyieliberoit sat apr 26 154931 2008 message 7 date tue 4 mar 2008 162022 0100 carmelo saffioti subject wekalist weka running slow windows vista weka machine learning workbench list messageid 004101c87e0b443fefc06e0000c0carmelo contenttype textplain charsetiso88591 hello im trying use weka new windows vista running really slow startup takes 47 seconds need use fileopen dialog takes many seconds launching weka command line java verbose option discovered startup waits sunawtshellwin32shellfolder2folderdisposer1 dprogrammijavajre1604librtjar please help solve problem need use weka vista thank much cheers carmelo next part html attachment scrubbed url httpslistscmswaikatoacnzpipermailwekalistattachments20080304a2aea18battachment0001html fri 08 aug 2008 033626 0500 wekalist digest vol 61 issue 2