m9 vevrry4iaenl begin pgp signed message hash sha1 cristian rodríguez schreef alexey eremenko escribió hi installed opensuse 110 highly ridiculous expect alpha product ready matter fact a1 seemed ready a2 might cause around time realy new things added nice day m9 time exists os linux 26221701default x86_64 huidige gebruiker monkey9amd64x2sfn1 systeem opensuse 103 x86_64 kde 357 release 726 begin pgp signature version gnupg v204svn0 gnulinux comment using gnupg suse httpenigmailmozdevorg id8dbqfhtfqax5x5x6lpdgrahvsakctg52xvd8vkydrznlszvav5dukagcbbxgv qgtkhwkgd2rrb2h0rjh6zm txrl end pgp signature dlnirllccswaikatoacnz sun feb 24 103133 2008 message 1 date sat 16 feb 2008 144450 1300 nzdt peter reutemann subject wekalist questions experimenter weka machine learning workbench list messageid 4444540884010391444454088sujmdnjkwebmailscmswaikatoacnz contenttype textplaincharset3diso88591 sure way seperate experiment results one database able achieve everything seems go results0 table automatically use different mysql database experiment want keep seperated experiment setup ie crossvalidationpercentagesplit randomizedfixed parameters defines single experiment basically soon cant compare anymore cant compare crossvalidation percentagesplit results 2fold 10fold cv results directed another table always use setup need create different databases like create different output files 3 one shows summary ranking lot pairwise significance tests used tests bonferroni adjusted corrected shown paired ttest indicate bonferroni correction multiple significance tests different kind correction copypaste wekaexperimentpairedcorrectedttester javadoc behaves pairedttester uses corrected resampled ttest statistic information see claude nadeau yoshua bengio 2001 inference generalization error machine learning dug far little understanding statistics goes corrected ttest corrects underestimate variance one repeated cvs seems automatic bonferroni adjustment least nowhere mentioned weka sorry statistics knowledge even less hth cheers peter peter reutemann dept computer science university waikato nz httpwwwcswaikatoacnzfracpete ph 64 7 8585174 greljzktpquktddhelsinkifi sun feb 24 103133 2008 message 2 date sat 16 feb 2008 114053 0200 harri mt saarikoski subject wekalist question feature selection weka machine learning workbench list messageid 120315485347b6afa57b1c4webmailhelsinkifi contenttype textplain charset3dusascii lainaus fang wang hello recently feature selection classification example gene list gene contains 15 features weka using filter get 5 features among initial 15 fetures 5 features using supervised classifer could seperate genes cancerrelated noncancerrelated want use 5 features scan another group genes want try find cancer related brief sentence question 1a list genes gene 15 features already know cancer related 2a list genes investigate gene feature genes idea cancer related genes hi able reduce dimensions five features want classify cancerno extent features predicts instance think sensible classifier naive bayes decision trees instancebased classifier ibk deliver optimal accuracy 95 least found possible mark classes new gene instances test set use crossvalidation 10fold cv explorer recommendedly 10 times 10fold cv experimenter possible unexpected problem come iterative classifiers support vector machines smo libsvm errorminimizing neural network multilayerperceptron possible key parameters set tight even though cv error close zero test error may tend make generalizations carsinogeny value ranges features svm problem comes support vectors instances mark class border defined clearly ie instances highly ambiguous basically could consider using svm several local maxima per feature ie ranges 010 80100 1080 correlated cancer since svm evaluate features part whole instances neural networks problem stop iteration feature weight changes hard estimate lead overfitting ie incorrect feature weights anyway set learning rate parameter high dataset require many iterations low generalization accuracy tend happen stable classifiers naive bayes instancebased classifier lazyibk eg j48 confidence parameter set maximum 050 performs pruning tree basically decision tree trees package therefore would safer choice expect five features work together predict cancer consider bayesnet place naive bayes since assumes features correlated harri suggestion idea question appreciated thanks fang wang _______________________________________________ wekalist mailing list iuxxdkqklistscmswaikatoacnz httpslistscmswaikatoacnzmailmanlistinfowekalist yst terv best wishes harri saarikoski yruyieliberoit sun feb 24 103133 2008 message 3 date sun 17 feb 2008 111117 0100 carmelo saffioti subject wekalist weka models pmml weka machine learning workbench list messageid 003d01c8714d6ff0c6506e0000c0carmelo contenttype textplain charset3diso88591 hi possible export weka models pmml predictive model markup lan guage format would great thing would possible share weka models data mining suites thanks carmelo next part html attachment scrubbed url httpslistscmswaikatoacnzpipermailwekalistattachments2008021 78b28a046attachment0001html yruyieliberoit sun feb 24 103133 2008 message 4 date sun 17 feb 2008 120444 0100 carmelo saffioti subject wekalist memory independent algorithms weka machine learning workbench list messageid 005701c87154e7190fb06e0000c0carmelo contenttype textplain charset3diso88591 hi im working huge datasets ive got often problems memory b ecause required huge memory work datasets possib le use memory independent algorithms weka saw data mini ng suites make model training directly data read dataset thanks carmelo next part html attachment scrubbed url httpslistscmswaikatoacnzpipermailwekalistattachments2008021 78b7d1de2attachment0001html dnrxv_ttnxyahoocom sun feb 24 103133 2008 message 5 date sun 17 feb 2008 051742 0800 pst rafiqul haque subject wekalist ignoring attribute iuxxdkqklistscmswaikatoacnz messageid 94064714732qmweb30005mailmudyahoocom contenttype textplain charset3diso88591 dear experts asked ignore attributes using command line instead selecting ignore attribute window ignore attribute using command line weka thanking advance _____________________________________________________________________ _______________ looking last minute shopping deals find fast yahoo search httptoolssearchyahoocomnewsearch categoryphpcategory3dshopping dlnirllccswaikatoacnz sun feb 24 103133 2008 message 6 date mon 18 feb 2008 090137 1300 nzdt peter reutemann subject wekalist memory independent algorithms weka machine learning workbench list messageid 9621551132543655962155113wjwhgtxpwebmailscmswaikatoacnz contenttype textplaincharset3diso88591 im working huge datasets ive got often problems memory required huge memory work datasets possible use memory independent algorithms weka saw data mining suites make model training directly data read dataset incremental schemes weka check javadoc wekaclassifiersupdateableclassifier lists algorithms implementing interface hth cheers peter peter reutemann dept computer science university waikato nz httpwwwcswaikatoacnzfracpete ph 64 7 8585174 dlnirllccswaikatoacnz sun feb 24 103133 2008 message 7 date mon 18 feb 2008 091136 1300 nzdt peter reutemann subject wekalist ignoring attribute weka machine learning workbench list messageid 9352308749061819935230874pwyfsjfrwebmailscmswaikatoacnz contenttype textplaincharset3diso88591 asked ignore attributes using command line instead selecting ignore attribute window ignore attribute using command line weka assume youre using cluster algorithm commandline doesnt support general ignoring attributes explorer uses following filter ignoring attributes creates copy dataset removes selected attributes copy passing cluster algorithm wekafiltersunsupervisedattributeremove use filter conjunction wekaclusterersfilteredclusterer metaclusterer developer version since 354 see javadoc information hth cheers peter peter reutemann dept computer science university waikato nz httpwwwcswaikatoacnzfracpete ph 64 7 8585174 dlnirllccswaikatoacnz sun feb 24 103133 2008 message 8 date mon 18 feb 2008 085701 1300 nzdt peter reutemann subject wekalist weka models pmml weka machine learning workbench list messageid 7785907874113373778590787ezttrnjlwebmailscmswaikatoacnz contenttype textplaincharset3diso88591 possible export weka models pmml predictive model markup language format would great thing would possible share weka models data mining suites moment cheers peter peter reutemann dept computer science university waikato nz httpwwwcswaikatoacnzfracpete ph 64 7 8585174 vafzspentahoorg sun feb 24 103133 2008 message 9 date mon 18 feb 2008 100500 1300 mark hall subject wekalist knowledge flow interface clustering variables input clustering algorithm kept reassociated result clustering weka machine learning workbench list messageid 20080217210500gb9517cygnuslocal contenttype textplain charset3dusascii yes using filteredclusterer knowledgeflow set filter removefilter order remove attributes dont want clusterer see connect predictionappender attributes still present data along predicted cluster visualization etc cheers mark thu feb 14 2008 060819pm 0000 john black wrote anyone help one please clustering explorer interface weka possible view save cluster assignments even though variable excluded clustering algorithm using ignore attributes button present cluster allocation information saved nominal variables data set may useful analysing results clustering want keep variables inputting clustering algorithm however using knowledge flow interface nominal variables excluded using remove function anyone know way weka knowledge flow interface achieve thing outlined happens explorer interface ie keep variables excluded clustering data set somehow reattach removed many thanks help john black _______________________________________________ wekalist mailing list iuxxdkqklistscmswaikatoacnz httpslistscmswaikatoacnzmailmanlistinfowekalist mark hall senior developerconsultant pentaho open source business intelligence company citadel international suite 340 5950 hazeltine national dr orlando fl 32822 usa 5 grace avenue hamilton 3210 new zealand 64 7 8473537 office 64 21 399132 mobile 1 815 5508637 fax skype markandrewhall yahoo mark_andrew_hall download latest release today _______________________________________________ wekalist mailing list iuxxdkqklistscmswaikatoacnz httpslistscmswaikatoacnzmailmanlistinfowekalist wed 06 aug 2008 014600 0100 opensuse opensuse 110 nonready kde4