http://git-wip-us.apache.org/repos/asf/incubator-hivemall-site/blob/ba518dab/userguide/binaryclass/a9a_minibatch.html ---------------------------------------------------------------------- diff --git a/userguide/binaryclass/a9a_minibatch.html b/userguide/binaryclass/a9a_minibatch.html index b302cee..50f5dba 100644 --- a/userguide/binaryclass/a9a_minibatch.html +++ b/userguide/binaryclass/a9a_minibatch.html @@ -598,14 +598,30 @@ </li> - <li class="chapter " data-level="3.5" data-path="../ft_engineering/tfidf.html"> + <li class="chapter " data-level="3.5" data-path="../ft_engineering/pairing.html"> - <a href="../ft_engineering/tfidf.html"> + <a href="../ft_engineering/pairing.html"> <b>3.5.</b> - TF-IDF Calculation + FEATURE PAIRING + + </a> + + + + <ul class="articles"> + + + <li class="chapter " data-level="3.5.1" data-path="../ft_engineering/polynomial.html"> + + <a href="../ft_engineering/polynomial.html"> + + + <b>3.5.1.</b> + + Polynomial Features </a> @@ -613,6 +629,11 @@ </li> + + </ul> + + </li> + <li class="chapter " data-level="3.6" data-path="../ft_engineering/ft_trans.html"> <a href="../ft_engineering/ft_trans.html"> @@ -664,6 +685,21 @@ </li> + <li class="chapter " data-level="3.7" data-path="../ft_engineering/tfidf.html"> + + <a href="../ft_engineering/tfidf.html"> + + + <b>3.7.</b> + + TF-IDF Calculation + + </a> + + + + </li> + @@ -761,7 +797,7 @@ - <li class="header">Part V - Prediction</li> + <li class="header">Part V - Supervised Learning</li> @@ -780,27 +816,19 @@ </li> - <li class="chapter " data-level="5.2" data-path="../regression/general.html"> - - <a href="../regression/general.html"> - - - <b>5.2.</b> - - Regression - - </a> - - - </li> - <li class="chapter " data-level="5.3" data-path="general.html"> + + <li class="header">Part VI - Binary classification</li> + + + + <li class="chapter " data-level="6.1" data-path="general.html"> <a href="general.html"> - <b>5.3.</b> + <b>6.1.</b> Binary Classification @@ -810,21 +838,14 @@ </li> - - - - <li class="header">Part VI - Binary classification tutorials</li> - - - - <li class="chapter " data-level="6.1" data-path="a9a.html"> + <li class="chapter " data-level="6.2" data-path="a9a.html"> <a href="a9a.html"> - <b>6.1.</b> + <b>6.2.</b> - a9a + a9a tutorial </a> @@ -833,12 +854,12 @@ <ul class="articles"> - <li class="chapter " data-level="6.1.1" data-path="a9a_dataset.html"> + <li class="chapter " data-level="6.2.1" data-path="a9a_dataset.html"> <a href="a9a_dataset.html"> - <b>6.1.1.</b> + <b>6.2.1.</b> Data preparation @@ -848,12 +869,12 @@ </li> - <li class="chapter " data-level="6.1.2" data-path="a9a_lr.html"> + <li class="chapter " data-level="6.2.2" data-path="a9a_lr.html"> <a href="a9a_lr.html"> - <b>6.1.2.</b> + <b>6.2.2.</b> Logistic Regression @@ -863,12 +884,12 @@ </li> - <li class="chapter active" data-level="6.1.3" data-path="a9a_minibatch.html"> + <li class="chapter active" data-level="6.2.3" data-path="a9a_minibatch.html"> <a href="a9a_minibatch.html"> - <b>6.1.3.</b> + <b>6.2.3.</b> Mini-batch Gradient Descent @@ -883,14 +904,14 @@ </li> - <li class="chapter " data-level="6.2" data-path="news20.html"> + <li class="chapter " data-level="6.3" data-path="news20.html"> <a href="news20.html"> - <b>6.2.</b> + <b>6.3.</b> - News20 + News20 tutorial </a> @@ -899,12 +920,12 @@ <ul class="articles"> - <li class="chapter " data-level="6.2.1" data-path="news20_dataset.html"> + <li class="chapter " data-level="6.3.1" data-path="news20_dataset.html"> <a href="news20_dataset.html"> - <b>6.2.1.</b> + <b>6.3.1.</b> Data preparation @@ -914,12 +935,12 @@ </li> - <li class="chapter " data-level="6.2.2" data-path="news20_pa.html"> + <li class="chapter " data-level="6.3.2" data-path="news20_pa.html"> <a href="news20_pa.html"> - <b>6.2.2.</b> + <b>6.3.2.</b> Perceptron, Passive Aggressive @@ -929,12 +950,12 @@ </li> - <li class="chapter " data-level="6.2.3" data-path="news20_scw.html"> + <li class="chapter " data-level="6.3.3" data-path="news20_scw.html"> <a href="news20_scw.html"> - <b>6.2.3.</b> + <b>6.3.3.</b> CW, AROW, SCW @@ -944,12 +965,12 @@ </li> - <li class="chapter " data-level="6.2.4" data-path="news20_adagrad.html"> + <li class="chapter " data-level="6.3.4" data-path="news20_adagrad.html"> <a href="news20_adagrad.html"> - <b>6.2.4.</b> + <b>6.3.4.</b> AdaGradRDA, AdaGrad, AdaDelta @@ -964,14 +985,14 @@ </li> - <li class="chapter " data-level="6.3" data-path="kdd2010a.html"> + <li class="chapter " data-level="6.4" data-path="kdd2010a.html"> <a href="kdd2010a.html"> - <b>6.3.</b> + <b>6.4.</b> - KDD2010a + KDD2010a tutorial </a> @@ -980,12 +1001,12 @@ <ul class="articles"> - <li class="chapter " data-level="6.3.1" data-path="kdd2010a_dataset.html"> + <li class="chapter " data-level="6.4.1" data-path="kdd2010a_dataset.html"> <a href="kdd2010a_dataset.html"> - <b>6.3.1.</b> + <b>6.4.1.</b> Data preparation @@ -995,12 +1016,12 @@ </li> - <li class="chapter " data-level="6.3.2" data-path="kdd2010a_scw.html"> + <li class="chapter " data-level="6.4.2" data-path="kdd2010a_scw.html"> <a href="kdd2010a_scw.html"> - <b>6.3.2.</b> + <b>6.4.2.</b> PA, CW, AROW, SCW @@ -1015,14 +1036,14 @@ </li> - <li class="chapter " data-level="6.4" data-path="kdd2010b.html"> + <li class="chapter " data-level="6.5" data-path="kdd2010b.html"> <a href="kdd2010b.html"> - <b>6.4.</b> + <b>6.5.</b> - KDD2010b + KDD2010b tutorial </a> @@ -1031,12 +1052,12 @@ <ul class="articles"> - <li class="chapter " data-level="6.4.1" data-path="kdd2010b_dataset.html"> + <li class="chapter " data-level="6.5.1" data-path="kdd2010b_dataset.html"> <a href="kdd2010b_dataset.html"> - <b>6.4.1.</b> + <b>6.5.1.</b> Data preparation @@ -1046,12 +1067,12 @@ </li> - <li class="chapter " data-level="6.4.2" data-path="kdd2010b_arow.html"> + <li class="chapter " data-level="6.5.2" data-path="kdd2010b_arow.html"> <a href="kdd2010b_arow.html"> - <b>6.4.2.</b> + <b>6.5.2.</b> AROW @@ -1066,14 +1087,14 @@ </li> - <li class="chapter " data-level="6.5" data-path="webspam.html"> + <li class="chapter " data-level="6.6" data-path="webspam.html"> <a href="webspam.html"> - <b>6.5.</b> + <b>6.6.</b> - Webspam + Webspam tutorial </a> @@ -1082,12 +1103,12 @@ <ul class="articles"> - <li class="chapter " data-level="6.5.1" data-path="webspam_dataset.html"> + <li class="chapter " data-level="6.6.1" data-path="webspam_dataset.html"> <a href="webspam_dataset.html"> - <b>6.5.1.</b> + <b>6.6.1.</b> Data pareparation @@ -1097,12 +1118,12 @@ </li> - <li class="chapter " data-level="6.5.2" data-path="webspam_scw.html"> + <li class="chapter " data-level="6.6.2" data-path="webspam_scw.html"> <a href="webspam_scw.html"> - <b>6.5.2.</b> + <b>6.6.2.</b> PA1, AROW, SCW @@ -1117,14 +1138,14 @@ </li> - <li class="chapter " data-level="6.6" data-path="titanic_rf.html"> + <li class="chapter " data-level="6.7" data-path="titanic_rf.html"> <a href="titanic_rf.html"> - <b>6.6.</b> + <b>6.7.</b> - Kaggle Titanic + Kaggle Titanic tutorial </a> @@ -1135,7 +1156,7 @@ - <li class="header">Part VII - Multiclass classification tutorials</li> + <li class="header">Part VII - Multiclass classification</li> @@ -1146,7 +1167,7 @@ <b>7.1.</b> - News20 Multiclass + News20 Multiclass tutorial </a> @@ -1257,7 +1278,7 @@ <b>7.2.</b> - Iris + Iris tutorial </a> @@ -1319,18 +1340,33 @@ - <li class="header">Part VIII - Regression tutorials</li> + <li class="header">Part VIII - Regression</li> - <li class="chapter " data-level="8.1" data-path="../regression/e2006.html"> + <li class="chapter " data-level="8.1" data-path="../regression/general.html"> - <a href="../regression/e2006.html"> + <a href="../regression/general.html"> <b>8.1.</b> - E2006-tfidf regression + Regression + + </a> + + + + </li> + + <li class="chapter " data-level="8.2" data-path="../regression/e2006.html"> + + <a href="../regression/e2006.html"> + + + <b>8.2.</b> + + E2006-tfidf regression tutorial </a> @@ -1339,12 +1375,12 @@ <ul class="articles"> - <li class="chapter " data-level="8.1.1" data-path="../regression/e2006_dataset.html"> + <li class="chapter " data-level="8.2.1" data-path="../regression/e2006_dataset.html"> <a href="../regression/e2006_dataset.html"> - <b>8.1.1.</b> + <b>8.2.1.</b> Data preparation @@ -1354,12 +1390,12 @@ </li> - <li class="chapter " data-level="8.1.2" data-path="../regression/e2006_arow.html"> + <li class="chapter " data-level="8.2.2" data-path="../regression/e2006_arow.html"> <a href="../regression/e2006_arow.html"> - <b>8.1.2.</b> + <b>8.2.2.</b> Passive Aggressive, AROW @@ -1374,14 +1410,14 @@ </li> - <li class="chapter " data-level="8.2" data-path="../regression/kddcup12tr2.html"> + <li class="chapter " data-level="8.3" data-path="../regression/kddcup12tr2.html"> <a href="../regression/kddcup12tr2.html"> - <b>8.2.</b> + <b>8.3.</b> - KDDCup 2012 track 2 CTR prediction + KDDCup 2012 track 2 CTR prediction tutorial </a> @@ -1390,12 +1426,12 @@ <ul class="articles"> - <li class="chapter " data-level="8.2.1" data-path="../regression/kddcup12tr2_dataset.html"> + <li class="chapter " data-level="8.3.1" data-path="../regression/kddcup12tr2_dataset.html"> <a href="../regression/kddcup12tr2_dataset.html"> - <b>8.2.1.</b> + <b>8.3.1.</b> Data preparation @@ -1405,12 +1441,12 @@ </li> - <li class="chapter " data-level="8.2.2" data-path="../regression/kddcup12tr2_lr.html"> + <li class="chapter " data-level="8.3.2" data-path="../regression/kddcup12tr2_lr.html"> <a href="../regression/kddcup12tr2_lr.html"> - <b>8.2.2.</b> + <b>8.3.2.</b> Logistic Regression, Passive Aggressive @@ -1420,12 +1456,12 @@ </li> - <li class="chapter " data-level="8.2.3" data-path="../regression/kddcup12tr2_lr_amplify.html"> + <li class="chapter " data-level="8.3.3" data-path="../regression/kddcup12tr2_lr_amplify.html"> <a href="../regression/kddcup12tr2_lr_amplify.html"> - <b>8.2.3.</b> + <b>8.3.3.</b> Logistic Regression with Amplifier @@ -1435,12 +1471,12 @@ </li> - <li class="chapter " data-level="8.2.4" data-path="../regression/kddcup12tr2_adagrad.html"> + <li class="chapter " data-level="8.3.4" data-path="../regression/kddcup12tr2_adagrad.html"> <a href="../regression/kddcup12tr2_adagrad.html"> - <b>8.2.4.</b> + <b>8.3.4.</b> AdaGrad, AdaDelta @@ -2167,7 +2203,7 @@ Apache Hivemall is an effort undergoing incubation at The Apache Software Founda <script> var gitbook = gitbook || []; gitbook.push(function() { - gitbook.page.hasChanged({"page":{"title":"Mini-batch Gradient Descent","level":"6.1.3","depth":2,"next":{"title":"News20","level":"6.2","depth":1,"path":"binaryclass/news20.md","ref":"binaryclass/news20.md","articles":[{"title":"Data preparation","level":"6.2.1","depth":2,"path":"binaryclass/news20_dataset.md","ref":"binaryclass/news20_dataset.md","articles":[]},{"title":"Perceptron, Passive Aggressive","level":"6.2.2","depth":2,"path":"binaryclass/news20_pa.md","ref":"binaryclass/news20_pa.md","articles":[]},{"title":"CW, AROW, SCW","level":"6.2.3","depth":2,"path":"binaryclass/news20_scw.md","ref":"binaryclass/news20_scw.md","articles":[]},{"title":"AdaGradRDA, AdaGrad, AdaDelta","level":"6.2.4","depth":2,"path":"binaryclass/news20_adagrad.md","ref":"binaryclass/news20_adagrad.md","articles":[]}]},"previous":{"title":"Logistic Regression","level":"6.1.2","depth":2,"path":"binaryclass/a9a_lr.md","ref":"binaryclass/a9a_lr.md","articles":[]},"dir":"ltr"},"config":{"plugin s":["theme-api","edit-link","github","splitter","sitemap","etoc","callouts","toggle-chapters","anchorjs","codeblock-filename","expandable-chapters","multipart","codeblock-filename","katex","emphasize","localized-footer"],"styles":{"website":"styles/website.css","pdf":"styles/pdf.css","epub":"styles/epub.css","mobi":"styles/mobi.css","ebook":"styles/ebook.css","print":"styles/print.css"},"pluginsConfig":{"emphasize":{},"callouts":{},"etoc":{"h2lb":3,"header":1,"maxdepth":3,"mindepth":1,"notoc":true},"github":{"url":"https://github.com/apache/incubator-hivemall/"},"splitter":{},"search":{},"downloadpdf":{"base":"https://github.com/apache/incubator-hivemall/docs/gitbook","label":"PDF","multilingual":false},"multipart":{},"localized-footer":{"filename":"FOOTER.md","hline":"true"},"lunr":{"maxIndexSize":1000000,"ignoreSpecialCharacters":false},"katex":{},"fontsettings":{"theme":"white","family":"sans","size":2,"font":"sans"},"highlight":{},"codeblock-filename":{},"sitemap":{"hostname":"h ttp://hivemall.incubator.apache.org/"},"theme-api":{"languages":[],"split":false,"theme":"dark"},"sharing":{"facebook":true,"twitter":true,"google":false,"weibo":false,"instapaper":false,"vk":false,"all":["facebook","google","twitter","weibo","instapaper"]},"edit-link":{"label":"Edit","base":"https://github.com/apache/incubator-hivemall/docs/gitbook"},"theme-default":{"styles":{"website":"styles/website.css","pdf":"styles/pdf.css","epub":"styles/epub.css","mobi":"styles/mobi.css","ebook":"styles/ebook.css","print":"styles/print.css"},"showLevel":true},"anchorjs":{"selector":"h1,h2,h3,*:not(.callout) > h4,h5"},"toggle-chapters":{},"expandable-chapters":{}},"theme":"default","pdf":{"pageNumbers":true,"fontSize":12,"fontFamily":"Arial","paperSize":"a4","chapterMark":"pagebreak","pageBreaksBefore":"/","margin":{"right":62,"left":62,"top":56,"bottom":56}},"structure":{"langs":"LANGS.md","readme":"README.md","glossary":"GLOSSARY.md","summary":"SUMMARY.md"},"variables":{},"title":"Hivemall User Manual","links":{"sidebar":{"<i class=\"fa fa-home\"></i> Home":"http://hivemall.incubator.apache.org/"}},"gitbook":"3.x.x","description":"User Manual for Apache Hivemall"},"file":{"path":"binaryclass/a9a_minibatch.md","mtime":"2017-02-08T07:24:57.000Z","type":"markdown"},"gitbook":{"version":"3.2.2","time":"2017-06-15T10:33:21.138Z"},"basePath":"..","book":{"language":""}}); + gitbook.page.hasChanged({"page":{"title":"Mini-batch Gradient Descent","level":"6.2.3","depth":2,"next":{"title":"News20 tutorial","level":"6.3","depth":1,"path":"binaryclass/news20.md","ref":"binaryclass/news20.md","articles":[{"title":"Data preparation","level":"6.3.1","depth":2,"path":"binaryclass/news20_dataset.md","ref":"binaryclass/news20_dataset.md","articles":[]},{"title":"Perceptron, Passive Aggressive","level":"6.3.2","depth":2,"path":"binaryclass/news20_pa.md","ref":"binaryclass/news20_pa.md","articles":[]},{"title":"CW, AROW, SCW","level":"6.3.3","depth":2,"path":"binaryclass/news20_scw.md","ref":"binaryclass/news20_scw.md","articles":[]},{"title":"AdaGradRDA, AdaGrad, AdaDelta","level":"6.3.4","depth":2,"path":"binaryclass/news20_adagrad.md","ref":"binaryclass/news20_adagrad.md","articles":[]}]},"previous":{"title":"Logistic Regression","level":"6.2.2","depth":2,"path":"binaryclass/a9a_lr.md","ref":"binaryclass/a9a_lr.md","articles":[]},"dir":"ltr"},"config" :{"plugins":["theme-api","edit-link","github","splitter","sitemap","etoc","callouts","toggle-chapters","anchorjs","codeblock-filename","expandable-chapters","multipart","codeblock-filename","katex","emphasize","localized-footer"],"styles":{"website":"styles/website.css","pdf":"styles/pdf.css","epub":"styles/epub.css","mobi":"styles/mobi.css","ebook":"styles/ebook.css","print":"styles/print.css"},"pluginsConfig":{"emphasize":{},"callouts":{},"etoc":{"h2lb":3,"header":1,"maxdepth":3,"mindepth":1,"notoc":true},"github":{"url":"https://github.com/apache/incubator-hivemall/"},"splitter":{},"search":{},"downloadpdf":{"base":"https://github.com/apache/incubator-hivemall/docs/gitbook","label":"PDF","multilingual":false},"multipart":{},"localized-footer":{"filename":"FOOTER.md","hline":"true"},"lunr":{"maxIndexSize":1000000,"ignoreSpecialCharacters":false},"katex":{},"fontsettings":{"theme":"white","family":"sans","size":2,"font":"sans"},"highlight":{},"codeblock-filename":{},"sitemap":{"hos tname":"http://hivemall.incubator.apache.org/"},"theme-api":{"languages":[],"split":false,"theme":"dark"},"sharing":{"facebook":true,"twitter":true,"google":false,"weibo":false,"instapaper":false,"vk":false,"all":["facebook","google","twitter","weibo","instapaper"]},"edit-link":{"label":"Edit","base":"https://github.com/apache/incubator-hivemall/docs/gitbook"},"theme-default":{"styles":{"website":"styles/website.css","pdf":"styles/pdf.css","epub":"styles/epub.css","mobi":"styles/mobi.css","ebook":"styles/ebook.css","print":"styles/print.css"},"showLevel":true},"anchorjs":{"selector":"h1,h2,h3,*:not(.callout) > h4,h5"},"toggle-chapters":{},"expandable-chapters":{}},"theme":"default","pdf":{"pageNumbers":true,"fontSize":12,"fontFamily":"Arial","paperSize":"a4","chapterMark":"pagebreak","pageBreaksBefore":"/","margin":{"right":62,"left":62,"top":56,"bottom":56}},"structure":{"langs":"LANGS.md","readme":"README.md","glossary":"GLOSSARY.md","summary":"SUMMARY.md"},"variables":{},"title": "Hivemall User Manual","links":{"sidebar":{"<i class=\"fa fa-home\"></i> Home":"http://hivemall.incubator.apache.org/"}},"gitbook":"3.x.x","description":"User Manual for Apache Hivemall"},"file":{"path":"binaryclass/a9a_minibatch.md","mtime":"2016-12-02T08:02:42.000Z","type":"markdown"},"gitbook":{"version":"3.2.2","time":"2017-06-23T09:59:20.878Z"},"basePath":"..","book":{"language":""}}); }); </script> </div>
http://git-wip-us.apache.org/repos/asf/incubator-hivemall-site/blob/ba518dab/userguide/binaryclass/general.html ---------------------------------------------------------------------- diff --git a/userguide/binaryclass/general.html b/userguide/binaryclass/general.html index 60d6d51..7917c9d 100644 --- a/userguide/binaryclass/general.html +++ b/userguide/binaryclass/general.html @@ -100,7 +100,7 @@ <link rel="next" href="a9a.html" /> - <link rel="prev" href="../regression/general.html" /> + <link rel="prev" href="../misc/prediction.html" /> </head> @@ -598,14 +598,30 @@ </li> - <li class="chapter " data-level="3.5" data-path="../ft_engineering/tfidf.html"> + <li class="chapter " data-level="3.5" data-path="../ft_engineering/pairing.html"> - <a href="../ft_engineering/tfidf.html"> + <a href="../ft_engineering/pairing.html"> <b>3.5.</b> - TF-IDF Calculation + FEATURE PAIRING + + </a> + + + + <ul class="articles"> + + + <li class="chapter " data-level="3.5.1" data-path="../ft_engineering/polynomial.html"> + + <a href="../ft_engineering/polynomial.html"> + + + <b>3.5.1.</b> + + Polynomial Features </a> @@ -613,6 +629,11 @@ </li> + + </ul> + + </li> + <li class="chapter " data-level="3.6" data-path="../ft_engineering/ft_trans.html"> <a href="../ft_engineering/ft_trans.html"> @@ -664,6 +685,21 @@ </li> + <li class="chapter " data-level="3.7" data-path="../ft_engineering/tfidf.html"> + + <a href="../ft_engineering/tfidf.html"> + + + <b>3.7.</b> + + TF-IDF Calculation + + </a> + + + + </li> + @@ -761,7 +797,7 @@ - <li class="header">Part V - Prediction</li> + <li class="header">Part V - Supervised Learning</li> @@ -780,27 +816,19 @@ </li> - <li class="chapter " data-level="5.2" data-path="../regression/general.html"> - - <a href="../regression/general.html"> - - - <b>5.2.</b> - - Regression - - </a> - - - </li> - <li class="chapter active" data-level="5.3" data-path="general.html"> + + <li class="header">Part VI - Binary classification</li> + + + + <li class="chapter active" data-level="6.1" data-path="general.html"> <a href="general.html"> - <b>5.3.</b> + <b>6.1.</b> Binary Classification @@ -810,21 +838,14 @@ </li> - - - - <li class="header">Part VI - Binary classification tutorials</li> - - - - <li class="chapter " data-level="6.1" data-path="a9a.html"> + <li class="chapter " data-level="6.2" data-path="a9a.html"> <a href="a9a.html"> - <b>6.1.</b> + <b>6.2.</b> - a9a + a9a tutorial </a> @@ -833,12 +854,12 @@ <ul class="articles"> - <li class="chapter " data-level="6.1.1" data-path="a9a_dataset.html"> + <li class="chapter " data-level="6.2.1" data-path="a9a_dataset.html"> <a href="a9a_dataset.html"> - <b>6.1.1.</b> + <b>6.2.1.</b> Data preparation @@ -848,12 +869,12 @@ </li> - <li class="chapter " data-level="6.1.2" data-path="a9a_lr.html"> + <li class="chapter " data-level="6.2.2" data-path="a9a_lr.html"> <a href="a9a_lr.html"> - <b>6.1.2.</b> + <b>6.2.2.</b> Logistic Regression @@ -863,12 +884,12 @@ </li> - <li class="chapter " data-level="6.1.3" data-path="a9a_minibatch.html"> + <li class="chapter " data-level="6.2.3" data-path="a9a_minibatch.html"> <a href="a9a_minibatch.html"> - <b>6.1.3.</b> + <b>6.2.3.</b> Mini-batch Gradient Descent @@ -883,14 +904,14 @@ </li> - <li class="chapter " data-level="6.2" data-path="news20.html"> + <li class="chapter " data-level="6.3" data-path="news20.html"> <a href="news20.html"> - <b>6.2.</b> + <b>6.3.</b> - News20 + News20 tutorial </a> @@ -899,12 +920,12 @@ <ul class="articles"> - <li class="chapter " data-level="6.2.1" data-path="news20_dataset.html"> + <li class="chapter " data-level="6.3.1" data-path="news20_dataset.html"> <a href="news20_dataset.html"> - <b>6.2.1.</b> + <b>6.3.1.</b> Data preparation @@ -914,12 +935,12 @@ </li> - <li class="chapter " data-level="6.2.2" data-path="news20_pa.html"> + <li class="chapter " data-level="6.3.2" data-path="news20_pa.html"> <a href="news20_pa.html"> - <b>6.2.2.</b> + <b>6.3.2.</b> Perceptron, Passive Aggressive @@ -929,12 +950,12 @@ </li> - <li class="chapter " data-level="6.2.3" data-path="news20_scw.html"> + <li class="chapter " data-level="6.3.3" data-path="news20_scw.html"> <a href="news20_scw.html"> - <b>6.2.3.</b> + <b>6.3.3.</b> CW, AROW, SCW @@ -944,12 +965,12 @@ </li> - <li class="chapter " data-level="6.2.4" data-path="news20_adagrad.html"> + <li class="chapter " data-level="6.3.4" data-path="news20_adagrad.html"> <a href="news20_adagrad.html"> - <b>6.2.4.</b> + <b>6.3.4.</b> AdaGradRDA, AdaGrad, AdaDelta @@ -964,14 +985,14 @@ </li> - <li class="chapter " data-level="6.3" data-path="kdd2010a.html"> + <li class="chapter " data-level="6.4" data-path="kdd2010a.html"> <a href="kdd2010a.html"> - <b>6.3.</b> + <b>6.4.</b> - KDD2010a + KDD2010a tutorial </a> @@ -980,12 +1001,12 @@ <ul class="articles"> - <li class="chapter " data-level="6.3.1" data-path="kdd2010a_dataset.html"> + <li class="chapter " data-level="6.4.1" data-path="kdd2010a_dataset.html"> <a href="kdd2010a_dataset.html"> - <b>6.3.1.</b> + <b>6.4.1.</b> Data preparation @@ -995,12 +1016,12 @@ </li> - <li class="chapter " data-level="6.3.2" data-path="kdd2010a_scw.html"> + <li class="chapter " data-level="6.4.2" data-path="kdd2010a_scw.html"> <a href="kdd2010a_scw.html"> - <b>6.3.2.</b> + <b>6.4.2.</b> PA, CW, AROW, SCW @@ -1015,14 +1036,14 @@ </li> - <li class="chapter " data-level="6.4" data-path="kdd2010b.html"> + <li class="chapter " data-level="6.5" data-path="kdd2010b.html"> <a href="kdd2010b.html"> - <b>6.4.</b> + <b>6.5.</b> - KDD2010b + KDD2010b tutorial </a> @@ -1031,12 +1052,12 @@ <ul class="articles"> - <li class="chapter " data-level="6.4.1" data-path="kdd2010b_dataset.html"> + <li class="chapter " data-level="6.5.1" data-path="kdd2010b_dataset.html"> <a href="kdd2010b_dataset.html"> - <b>6.4.1.</b> + <b>6.5.1.</b> Data preparation @@ -1046,12 +1067,12 @@ </li> - <li class="chapter " data-level="6.4.2" data-path="kdd2010b_arow.html"> + <li class="chapter " data-level="6.5.2" data-path="kdd2010b_arow.html"> <a href="kdd2010b_arow.html"> - <b>6.4.2.</b> + <b>6.5.2.</b> AROW @@ -1066,14 +1087,14 @@ </li> - <li class="chapter " data-level="6.5" data-path="webspam.html"> + <li class="chapter " data-level="6.6" data-path="webspam.html"> <a href="webspam.html"> - <b>6.5.</b> + <b>6.6.</b> - Webspam + Webspam tutorial </a> @@ -1082,12 +1103,12 @@ <ul class="articles"> - <li class="chapter " data-level="6.5.1" data-path="webspam_dataset.html"> + <li class="chapter " data-level="6.6.1" data-path="webspam_dataset.html"> <a href="webspam_dataset.html"> - <b>6.5.1.</b> + <b>6.6.1.</b> Data pareparation @@ -1097,12 +1118,12 @@ </li> - <li class="chapter " data-level="6.5.2" data-path="webspam_scw.html"> + <li class="chapter " data-level="6.6.2" data-path="webspam_scw.html"> <a href="webspam_scw.html"> - <b>6.5.2.</b> + <b>6.6.2.</b> PA1, AROW, SCW @@ -1117,14 +1138,14 @@ </li> - <li class="chapter " data-level="6.6" data-path="titanic_rf.html"> + <li class="chapter " data-level="6.7" data-path="titanic_rf.html"> <a href="titanic_rf.html"> - <b>6.6.</b> + <b>6.7.</b> - Kaggle Titanic + Kaggle Titanic tutorial </a> @@ -1135,7 +1156,7 @@ - <li class="header">Part VII - Multiclass classification tutorials</li> + <li class="header">Part VII - Multiclass classification</li> @@ -1146,7 +1167,7 @@ <b>7.1.</b> - News20 Multiclass + News20 Multiclass tutorial </a> @@ -1257,7 +1278,7 @@ <b>7.2.</b> - Iris + Iris tutorial </a> @@ -1319,18 +1340,33 @@ - <li class="header">Part VIII - Regression tutorials</li> + <li class="header">Part VIII - Regression</li> - <li class="chapter " data-level="8.1" data-path="../regression/e2006.html"> + <li class="chapter " data-level="8.1" data-path="../regression/general.html"> - <a href="../regression/e2006.html"> + <a href="../regression/general.html"> <b>8.1.</b> - E2006-tfidf regression + Regression + + </a> + + + + </li> + + <li class="chapter " data-level="8.2" data-path="../regression/e2006.html"> + + <a href="../regression/e2006.html"> + + + <b>8.2.</b> + + E2006-tfidf regression tutorial </a> @@ -1339,12 +1375,12 @@ <ul class="articles"> - <li class="chapter " data-level="8.1.1" data-path="../regression/e2006_dataset.html"> + <li class="chapter " data-level="8.2.1" data-path="../regression/e2006_dataset.html"> <a href="../regression/e2006_dataset.html"> - <b>8.1.1.</b> + <b>8.2.1.</b> Data preparation @@ -1354,12 +1390,12 @@ </li> - <li class="chapter " data-level="8.1.2" data-path="../regression/e2006_arow.html"> + <li class="chapter " data-level="8.2.2" data-path="../regression/e2006_arow.html"> <a href="../regression/e2006_arow.html"> - <b>8.1.2.</b> + <b>8.2.2.</b> Passive Aggressive, AROW @@ -1374,14 +1410,14 @@ </li> - <li class="chapter " data-level="8.2" data-path="../regression/kddcup12tr2.html"> + <li class="chapter " data-level="8.3" data-path="../regression/kddcup12tr2.html"> <a href="../regression/kddcup12tr2.html"> - <b>8.2.</b> + <b>8.3.</b> - KDDCup 2012 track 2 CTR prediction + KDDCup 2012 track 2 CTR prediction tutorial </a> @@ -1390,12 +1426,12 @@ <ul class="articles"> - <li class="chapter " data-level="8.2.1" data-path="../regression/kddcup12tr2_dataset.html"> + <li class="chapter " data-level="8.3.1" data-path="../regression/kddcup12tr2_dataset.html"> <a href="../regression/kddcup12tr2_dataset.html"> - <b>8.2.1.</b> + <b>8.3.1.</b> Data preparation @@ -1405,12 +1441,12 @@ </li> - <li class="chapter " data-level="8.2.2" data-path="../regression/kddcup12tr2_lr.html"> + <li class="chapter " data-level="8.3.2" data-path="../regression/kddcup12tr2_lr.html"> <a href="../regression/kddcup12tr2_lr.html"> - <b>8.2.2.</b> + <b>8.3.2.</b> Logistic Regression, Passive Aggressive @@ -1420,12 +1456,12 @@ </li> - <li class="chapter " data-level="8.2.3" data-path="../regression/kddcup12tr2_lr_amplify.html"> + <li class="chapter " data-level="8.3.3" data-path="../regression/kddcup12tr2_lr_amplify.html"> <a href="../regression/kddcup12tr2_lr_amplify.html"> - <b>8.2.3.</b> + <b>8.3.3.</b> Logistic Regression with Amplifier @@ -1435,12 +1471,12 @@ </li> - <li class="chapter " data-level="8.2.4" data-path="../regression/kddcup12tr2_adagrad.html"> + <li class="chapter " data-level="8.3.4" data-path="../regression/kddcup12tr2_adagrad.html"> <a href="../regression/kddcup12tr2_adagrad.html"> - <b>8.2.4.</b> + <b>8.3.4.</b> AdaGrad, AdaDelta @@ -2110,6 +2146,7 @@ ) t <span class="hljs-keyword">group</span> <span class="hljs-keyword">by</span> feature; </code></pre> +<div class="panel panel-primary"><div class="panel-heading"><h3 class="panel-title" id="note"><i class="fa fa-edit"></i> Note</h3></div><div class="panel-body"><p><code>-total_steps</code> option is an optional parameter and training works without it.</p></div></div> <h1 id="prediction--evaluation">Prediction & evaluation</h1> <pre><code class="lang-sql">WITH test_exploded as ( <span class="hljs-keyword">select</span> @@ -2124,7 +2161,7 @@ predict <span class="hljs-keyword">as</span> ( <span class="hljs-keyword">select</span> t.<span class="hljs-keyword">rowid</span>, sigmoid(<span class="hljs-keyword">sum</span>(m.weight * t.<span class="hljs-keyword">value</span>)) <span class="hljs-keyword">as</span> prob, - <span class="hljs-keyword">CAST</span>((<span class="hljs-keyword">case</span> <span class="hljs-keyword">when</span> sigmoid(<span class="hljs-keyword">sum</span>(m.weight * t.<span class="hljs-keyword">value</span>)) >= <span class="hljs-number">0.5</span> <span class="hljs-keyword">then</span> <span class="hljs-number">1.0</span> <span class="hljs-keyword">else</span> <span class="hljs-number">0.0</span> <span class="hljs-keyword">end</span>) <span class="hljs-keyword">as</span> <span class="hljs-built_in">FLOAT</span>) <span class="hljs-keyword">as</span> label + (<span class="hljs-keyword">case</span> <span class="hljs-keyword">when</span> sigmoid(<span class="hljs-keyword">sum</span>(m.weight * t.<span class="hljs-keyword">value</span>)) >= <span class="hljs-number">0.5</span> <span class="hljs-keyword">then</span> <span class="hljs-number">1.0</span> <span class="hljs-keyword">else</span> <span class="hljs-number">0.0</span> <span class="hljs-keyword">end</span>)<span class="hljs-keyword">as</span> label <span class="hljs-keyword">from</span> test_exploded t <span class="hljs-keyword">LEFT</span> <span class="hljs-keyword">OUTER</span> <span class="hljs-keyword">JOIN</span> classification_model m <span class="hljs-keyword">ON</span> (t.feature = m.feature) @@ -2229,7 +2266,7 @@ Apache Hivemall is an effort undergoing incubation at The Apache Software Founda <script> var gitbook = gitbook || []; gitbook.push(function() { - gitbook.page.hasChanged({"page":{"title":"Binary Classification","level":"5.3","depth":1,"next":{"title":"a9a","level":"6.1","depth":1,"path":"binaryclass/a9a.md","ref":"binaryclass/a9a.md","articles":[{"title":"Data preparation","level":"6.1.1","depth":2,"path":"binaryclass/a9a_dataset.md","ref":"binaryclass/a9a_dataset.md","articles":[]},{"title":"Logistic Regression","level":"6.1.2","depth":2,"path":"binaryclass/a9a_lr.md","ref":"binaryclass/a9a_lr.md","articles":[]},{"title":"Mini-batch Gradient Descent","level":"6.1.3","depth":2,"path":"binaryclass/a9a_minibatch.md","ref":"binaryclass/a9a_minibatch.md","articles":[]}]},"previous":{"title":"Regression","level":"5.2","depth":1,"path":"regression/general.md","ref":"regression/general.md","articles":[]},"dir":"ltr"},"config":{"plugins":["theme-api","edit-link","github","splitter","sitemap","etoc","callouts","toggle-chapters","anchorjs","codeblock-filename","expandable-chapters","multipart","codeblock-filename","katex"," emphasize","localized-footer"],"styles":{"website":"styles/website.css","pdf":"styles/pdf.css","epub":"styles/epub.css","mobi":"styles/mobi.css","ebook":"styles/ebook.css","print":"styles/print.css"},"pluginsConfig":{"emphasize":{},"callouts":{},"etoc":{"h2lb":3,"header":1,"maxdepth":3,"mindepth":1,"notoc":true},"github":{"url":"https://github.com/apache/incubator-hivemall/"},"splitter":{},"search":{},"downloadpdf":{"base":"https://github.com/apache/incubator-hivemall/docs/gitbook","label":"PDF","multilingual":false},"multipart":{},"localized-footer":{"filename":"FOOTER.md","hline":"true"},"lunr":{"maxIndexSize":1000000,"ignoreSpecialCharacters":false},"katex":{},"fontsettings":{"theme":"white","family":"sans","size":2,"font":"sans"},"highlight":{},"codeblock-filename":{},"sitemap":{"hostname":"http://hivemall.incubator.apache.org/"},"theme-api":{"languages":[],"split":false,"theme":"dark"},"sharing":{"facebook":true,"twitter":true,"google":false,"weibo":false,"instapaper":false,"vk ":false,"all":["facebook","google","twitter","weibo","instapaper"]},"edit-link":{"label":"Edit","base":"https://github.com/apache/incubator-hivemall/docs/gitbook"},"theme-default":{"styles":{"website":"styles/website.css","pdf":"styles/pdf.css","epub":"styles/epub.css","mobi":"styles/mobi.css","ebook":"styles/ebook.css","print":"styles/print.css"},"showLevel":true},"anchorjs":{"selector":"h1,h2,h3,*:not(.callout) > h4,h5"},"toggle-chapters":{},"expandable-chapters":{}},"theme":"default","pdf":{"pageNumbers":true,"fontSize":12,"fontFamily":"Arial","paperSize":"a4","chapterMark":"pagebreak","pageBreaksBefore":"/","margin":{"right":62,"left":62,"top":56,"bottom":56}},"structure":{"langs":"LANGS.md","readme":"README.md","glossary":"GLOSSARY.md","summary":"SUMMARY.md"},"variables":{},"title":"Hivemall User Manual","links":{"sidebar":{"<i class=\"fa fa-home\"></i> Home":"http://hivemall.incubator.apache.org/"}},"gitbook":"3.x.x","description":"User Manual for Apache Hivemall"},"file":{"pa th":"binaryclass/general.md","mtime":"2017-06-15T10:18:54.000Z","type":"markdown"},"gitbook":{"version":"3.2.2","time":"2017-06-15T10:33:21.138Z"},"basePath":"..","book":{"language":""}}); + gitbook.page.hasChanged({"page":{"title":"Binary Classification","level":"6.1","depth":1,"next":{"title":"a9a tutorial","level":"6.2","depth":1,"path":"binaryclass/a9a.md","ref":"binaryclass/a9a.md","articles":[{"title":"Data preparation","level":"6.2.1","depth":2,"path":"binaryclass/a9a_dataset.md","ref":"binaryclass/a9a_dataset.md","articles":[]},{"title":"Logistic Regression","level":"6.2.2","depth":2,"path":"binaryclass/a9a_lr.md","ref":"binaryclass/a9a_lr.md","articles":[]},{"title":"Mini-batch Gradient Descent","level":"6.2.3","depth":2,"path":"binaryclass/a9a_minibatch.md","ref":"binaryclass/a9a_minibatch.md","articles":[]}]},"previous":{"title":"How Prediction Works","level":"5.1","depth":1,"path":"misc/prediction.md","ref":"misc/prediction.md","articles":[]},"dir":"ltr"},"config":{"plugins":["theme-api","edit-link","github","splitter","sitemap","etoc","callouts","toggle-chapters","anchorjs","codeblock-filename","expandable-chapters","multipart","codeblock-filena me","katex","emphasize","localized-footer"],"styles":{"website":"styles/website.css","pdf":"styles/pdf.css","epub":"styles/epub.css","mobi":"styles/mobi.css","ebook":"styles/ebook.css","print":"styles/print.css"},"pluginsConfig":{"emphasize":{},"callouts":{},"etoc":{"h2lb":3,"header":1,"maxdepth":3,"mindepth":1,"notoc":true},"github":{"url":"https://github.com/apache/incubator-hivemall/"},"splitter":{},"search":{},"downloadpdf":{"base":"https://github.com/apache/incubator-hivemall/docs/gitbook","label":"PDF","multilingual":false},"multipart":{},"localized-footer":{"filename":"FOOTER.md","hline":"true"},"lunr":{"maxIndexSize":1000000,"ignoreSpecialCharacters":false},"katex":{},"fontsettings":{"theme":"white","family":"sans","size":2,"font":"sans"},"highlight":{},"codeblock-filename":{},"sitemap":{"hostname":"http://hivemall.incubator.apache.org/"},"theme-api":{"languages":[],"split":false,"theme":"dark"},"sharing":{"facebook":true,"twitter":true,"google":false,"weibo":false,"instapap er":false,"vk":false,"all":["facebook","google","twitter","weibo","instapaper"]},"edit-link":{"label":"Edit","base":"https://github.com/apache/incubator-hivemall/docs/gitbook"},"theme-default":{"styles":{"website":"styles/website.css","pdf":"styles/pdf.css","epub":"styles/epub.css","mobi":"styles/mobi.css","ebook":"styles/ebook.css","print":"styles/print.css"},"showLevel":true},"anchorjs":{"selector":"h1,h2,h3,*:not(.callout) > h4,h5"},"toggle-chapters":{},"expandable-chapters":{}},"theme":"default","pdf":{"pageNumbers":true,"fontSize":12,"fontFamily":"Arial","paperSize":"a4","chapterMark":"pagebreak","pageBreaksBefore":"/","margin":{"right":62,"left":62,"top":56,"bottom":56}},"structure":{"langs":"LANGS.md","readme":"README.md","glossary":"GLOSSARY.md","summary":"SUMMARY.md"},"variables":{},"title":"Hivemall User Manual","links":{"sidebar":{"<i class=\"fa fa-home\"></i> Home":"http://hivemall.incubator.apache.org/"}},"gitbook":"3.x.x","description":"User Manual for Apache Hivemall" },"file":{"path":"binaryclass/general.md","mtime":"2017-06-23T09:56:22.000Z","type":"markdown"},"gitbook":{"version":"3.2.2","time":"2017-06-23T09:59:20.878Z"},"basePath":"..","book":{"language":""}}); }); </script> </div> http://git-wip-us.apache.org/repos/asf/incubator-hivemall-site/blob/ba518dab/userguide/binaryclass/kdd2010a.html ---------------------------------------------------------------------- diff --git a/userguide/binaryclass/kdd2010a.html b/userguide/binaryclass/kdd2010a.html index 39aa385..29fd49b 100644 --- a/userguide/binaryclass/kdd2010a.html +++ b/userguide/binaryclass/kdd2010a.html @@ -4,7 +4,7 @@ <head> <meta charset="UTF-8"> <meta content="text/html; charset=utf-8" http-equiv="Content-Type"> - <title>KDD2010a · Hivemall User Manual</title> + <title>KDD2010a tutorial · Hivemall User Manual</title> <meta http-equiv="X-UA-Compatible" content="IE=edge" /> <meta name="description" content=""> <meta name="generator" content="GitBook 3.2.2"> @@ -598,14 +598,30 @@ </li> - <li class="chapter " data-level="3.5" data-path="../ft_engineering/tfidf.html"> + <li class="chapter " data-level="3.5" data-path="../ft_engineering/pairing.html"> - <a href="../ft_engineering/tfidf.html"> + <a href="../ft_engineering/pairing.html"> <b>3.5.</b> - TF-IDF Calculation + FEATURE PAIRING + + </a> + + + + <ul class="articles"> + + + <li class="chapter " data-level="3.5.1" data-path="../ft_engineering/polynomial.html"> + + <a href="../ft_engineering/polynomial.html"> + + + <b>3.5.1.</b> + + Polynomial Features </a> @@ -613,6 +629,11 @@ </li> + + </ul> + + </li> + <li class="chapter " data-level="3.6" data-path="../ft_engineering/ft_trans.html"> <a href="../ft_engineering/ft_trans.html"> @@ -664,6 +685,21 @@ </li> + <li class="chapter " data-level="3.7" data-path="../ft_engineering/tfidf.html"> + + <a href="../ft_engineering/tfidf.html"> + + + <b>3.7.</b> + + TF-IDF Calculation + + </a> + + + + </li> + @@ -761,7 +797,7 @@ - <li class="header">Part V - Prediction</li> + <li class="header">Part V - Supervised Learning</li> @@ -780,27 +816,19 @@ </li> - <li class="chapter " data-level="5.2" data-path="../regression/general.html"> - - <a href="../regression/general.html"> - - - <b>5.2.</b> - - Regression - - </a> - - - </li> - <li class="chapter " data-level="5.3" data-path="general.html"> + + <li class="header">Part VI - Binary classification</li> + + + + <li class="chapter " data-level="6.1" data-path="general.html"> <a href="general.html"> - <b>5.3.</b> + <b>6.1.</b> Binary Classification @@ -810,21 +838,14 @@ </li> - - - - <li class="header">Part VI - Binary classification tutorials</li> - - - - <li class="chapter " data-level="6.1" data-path="a9a.html"> + <li class="chapter " data-level="6.2" data-path="a9a.html"> <a href="a9a.html"> - <b>6.1.</b> + <b>6.2.</b> - a9a + a9a tutorial </a> @@ -833,12 +854,12 @@ <ul class="articles"> - <li class="chapter " data-level="6.1.1" data-path="a9a_dataset.html"> + <li class="chapter " data-level="6.2.1" data-path="a9a_dataset.html"> <a href="a9a_dataset.html"> - <b>6.1.1.</b> + <b>6.2.1.</b> Data preparation @@ -848,12 +869,12 @@ </li> - <li class="chapter " data-level="6.1.2" data-path="a9a_lr.html"> + <li class="chapter " data-level="6.2.2" data-path="a9a_lr.html"> <a href="a9a_lr.html"> - <b>6.1.2.</b> + <b>6.2.2.</b> Logistic Regression @@ -863,12 +884,12 @@ </li> - <li class="chapter " data-level="6.1.3" data-path="a9a_minibatch.html"> + <li class="chapter " data-level="6.2.3" data-path="a9a_minibatch.html"> <a href="a9a_minibatch.html"> - <b>6.1.3.</b> + <b>6.2.3.</b> Mini-batch Gradient Descent @@ -883,14 +904,14 @@ </li> - <li class="chapter " data-level="6.2" data-path="news20.html"> + <li class="chapter " data-level="6.3" data-path="news20.html"> <a href="news20.html"> - <b>6.2.</b> + <b>6.3.</b> - News20 + News20 tutorial </a> @@ -899,12 +920,12 @@ <ul class="articles"> - <li class="chapter " data-level="6.2.1" data-path="news20_dataset.html"> + <li class="chapter " data-level="6.3.1" data-path="news20_dataset.html"> <a href="news20_dataset.html"> - <b>6.2.1.</b> + <b>6.3.1.</b> Data preparation @@ -914,12 +935,12 @@ </li> - <li class="chapter " data-level="6.2.2" data-path="news20_pa.html"> + <li class="chapter " data-level="6.3.2" data-path="news20_pa.html"> <a href="news20_pa.html"> - <b>6.2.2.</b> + <b>6.3.2.</b> Perceptron, Passive Aggressive @@ -929,12 +950,12 @@ </li> - <li class="chapter " data-level="6.2.3" data-path="news20_scw.html"> + <li class="chapter " data-level="6.3.3" data-path="news20_scw.html"> <a href="news20_scw.html"> - <b>6.2.3.</b> + <b>6.3.3.</b> CW, AROW, SCW @@ -944,12 +965,12 @@ </li> - <li class="chapter " data-level="6.2.4" data-path="news20_adagrad.html"> + <li class="chapter " data-level="6.3.4" data-path="news20_adagrad.html"> <a href="news20_adagrad.html"> - <b>6.2.4.</b> + <b>6.3.4.</b> AdaGradRDA, AdaGrad, AdaDelta @@ -964,14 +985,14 @@ </li> - <li class="chapter active" data-level="6.3" data-path="kdd2010a.html"> + <li class="chapter active" data-level="6.4" data-path="kdd2010a.html"> <a href="kdd2010a.html"> - <b>6.3.</b> + <b>6.4.</b> - KDD2010a + KDD2010a tutorial </a> @@ -980,12 +1001,12 @@ <ul class="articles"> - <li class="chapter " data-level="6.3.1" data-path="kdd2010a_dataset.html"> + <li class="chapter " data-level="6.4.1" data-path="kdd2010a_dataset.html"> <a href="kdd2010a_dataset.html"> - <b>6.3.1.</b> + <b>6.4.1.</b> Data preparation @@ -995,12 +1016,12 @@ </li> - <li class="chapter " data-level="6.3.2" data-path="kdd2010a_scw.html"> + <li class="chapter " data-level="6.4.2" data-path="kdd2010a_scw.html"> <a href="kdd2010a_scw.html"> - <b>6.3.2.</b> + <b>6.4.2.</b> PA, CW, AROW, SCW @@ -1015,14 +1036,14 @@ </li> - <li class="chapter " data-level="6.4" data-path="kdd2010b.html"> + <li class="chapter " data-level="6.5" data-path="kdd2010b.html"> <a href="kdd2010b.html"> - <b>6.4.</b> + <b>6.5.</b> - KDD2010b + KDD2010b tutorial </a> @@ -1031,12 +1052,12 @@ <ul class="articles"> - <li class="chapter " data-level="6.4.1" data-path="kdd2010b_dataset.html"> + <li class="chapter " data-level="6.5.1" data-path="kdd2010b_dataset.html"> <a href="kdd2010b_dataset.html"> - <b>6.4.1.</b> + <b>6.5.1.</b> Data preparation @@ -1046,12 +1067,12 @@ </li> - <li class="chapter " data-level="6.4.2" data-path="kdd2010b_arow.html"> + <li class="chapter " data-level="6.5.2" data-path="kdd2010b_arow.html"> <a href="kdd2010b_arow.html"> - <b>6.4.2.</b> + <b>6.5.2.</b> AROW @@ -1066,14 +1087,14 @@ </li> - <li class="chapter " data-level="6.5" data-path="webspam.html"> + <li class="chapter " data-level="6.6" data-path="webspam.html"> <a href="webspam.html"> - <b>6.5.</b> + <b>6.6.</b> - Webspam + Webspam tutorial </a> @@ -1082,12 +1103,12 @@ <ul class="articles"> - <li class="chapter " data-level="6.5.1" data-path="webspam_dataset.html"> + <li class="chapter " data-level="6.6.1" data-path="webspam_dataset.html"> <a href="webspam_dataset.html"> - <b>6.5.1.</b> + <b>6.6.1.</b> Data pareparation @@ -1097,12 +1118,12 @@ </li> - <li class="chapter " data-level="6.5.2" data-path="webspam_scw.html"> + <li class="chapter " data-level="6.6.2" data-path="webspam_scw.html"> <a href="webspam_scw.html"> - <b>6.5.2.</b> + <b>6.6.2.</b> PA1, AROW, SCW @@ -1117,14 +1138,14 @@ </li> - <li class="chapter " data-level="6.6" data-path="titanic_rf.html"> + <li class="chapter " data-level="6.7" data-path="titanic_rf.html"> <a href="titanic_rf.html"> - <b>6.6.</b> + <b>6.7.</b> - Kaggle Titanic + Kaggle Titanic tutorial </a> @@ -1135,7 +1156,7 @@ - <li class="header">Part VII - Multiclass classification tutorials</li> + <li class="header">Part VII - Multiclass classification</li> @@ -1146,7 +1167,7 @@ <b>7.1.</b> - News20 Multiclass + News20 Multiclass tutorial </a> @@ -1257,7 +1278,7 @@ <b>7.2.</b> - Iris + Iris tutorial </a> @@ -1319,18 +1340,33 @@ - <li class="header">Part VIII - Regression tutorials</li> + <li class="header">Part VIII - Regression</li> - <li class="chapter " data-level="8.1" data-path="../regression/e2006.html"> + <li class="chapter " data-level="8.1" data-path="../regression/general.html"> - <a href="../regression/e2006.html"> + <a href="../regression/general.html"> <b>8.1.</b> - E2006-tfidf regression + Regression + + </a> + + + + </li> + + <li class="chapter " data-level="8.2" data-path="../regression/e2006.html"> + + <a href="../regression/e2006.html"> + + + <b>8.2.</b> + + E2006-tfidf regression tutorial </a> @@ -1339,12 +1375,12 @@ <ul class="articles"> - <li class="chapter " data-level="8.1.1" data-path="../regression/e2006_dataset.html"> + <li class="chapter " data-level="8.2.1" data-path="../regression/e2006_dataset.html"> <a href="../regression/e2006_dataset.html"> - <b>8.1.1.</b> + <b>8.2.1.</b> Data preparation @@ -1354,12 +1390,12 @@ </li> - <li class="chapter " data-level="8.1.2" data-path="../regression/e2006_arow.html"> + <li class="chapter " data-level="8.2.2" data-path="../regression/e2006_arow.html"> <a href="../regression/e2006_arow.html"> - <b>8.1.2.</b> + <b>8.2.2.</b> Passive Aggressive, AROW @@ -1374,14 +1410,14 @@ </li> - <li class="chapter " data-level="8.2" data-path="../regression/kddcup12tr2.html"> + <li class="chapter " data-level="8.3" data-path="../regression/kddcup12tr2.html"> <a href="../regression/kddcup12tr2.html"> - <b>8.2.</b> + <b>8.3.</b> - KDDCup 2012 track 2 CTR prediction + KDDCup 2012 track 2 CTR prediction tutorial </a> @@ -1390,12 +1426,12 @@ <ul class="articles"> - <li class="chapter " data-level="8.2.1" data-path="../regression/kddcup12tr2_dataset.html"> + <li class="chapter " data-level="8.3.1" data-path="../regression/kddcup12tr2_dataset.html"> <a href="../regression/kddcup12tr2_dataset.html"> - <b>8.2.1.</b> + <b>8.3.1.</b> Data preparation @@ -1405,12 +1441,12 @@ </li> - <li class="chapter " data-level="8.2.2" data-path="../regression/kddcup12tr2_lr.html"> + <li class="chapter " data-level="8.3.2" data-path="../regression/kddcup12tr2_lr.html"> <a href="../regression/kddcup12tr2_lr.html"> - <b>8.2.2.</b> + <b>8.3.2.</b> Logistic Regression, Passive Aggressive @@ -1420,12 +1456,12 @@ </li> - <li class="chapter " data-level="8.2.3" data-path="../regression/kddcup12tr2_lr_amplify.html"> + <li class="chapter " data-level="8.3.3" data-path="../regression/kddcup12tr2_lr_amplify.html"> <a href="../regression/kddcup12tr2_lr_amplify.html"> - <b>8.2.3.</b> + <b>8.3.3.</b> Logistic Regression with Amplifier @@ -1435,12 +1471,12 @@ </li> - <li class="chapter " data-level="8.2.4" data-path="../regression/kddcup12tr2_adagrad.html"> + <li class="chapter " data-level="8.3.4" data-path="../regression/kddcup12tr2_adagrad.html"> <a href="../regression/kddcup12tr2_adagrad.html"> - <b>8.2.4.</b> + <b>8.3.4.</b> AdaGrad, AdaDelta @@ -2041,7 +2077,7 @@ <!-- Title --> <h1> <i class="fa fa-circle-o-notch fa-spin"></i> - <a href=".." >KDD2010a</a> + <a href=".." >KDD2010a tutorial</a> </h1> </div> @@ -2129,7 +2165,7 @@ Apache Hivemall is an effort undergoing incubation at The Apache Software Founda <script> var gitbook = gitbook || []; gitbook.push(function() { - gitbook.page.hasChanged({"page":{"title":"KDD2010a","level":"6.3","depth":1,"next":{"title":"Data preparation","level":"6.3.1","depth":2,"path":"binaryclass/kdd2010a_dataset.md","ref":"binaryclass/kdd2010a_dataset.md","articles":[]},"previous":{"title":"AdaGradRDA, AdaGrad, AdaDelta","level":"6.2.4","depth":2,"path":"binaryclass/news20_adagrad.md","ref":"binaryclass/news20_adagrad.md","articles":[]},"dir":"ltr"},"config":{"plugins":["theme-api","edit-link","github","splitter","sitemap","etoc","callouts","toggle-chapters","anchorjs","codeblock-filename","expandable-chapters","multipart","codeblock-filename","katex","emphasize","localized-footer"],"styles":{"website":"styles/website.css","pdf":"styles/pdf.css","epub":"styles/epub.css","mobi":"styles/mobi.css","ebook":"styles/ebook.css","print":"styles/print.css"},"pluginsConfig":{"emphasize":{},"callouts":{},"etoc":{"h2lb":3,"header":1,"maxdepth":3,"mindepth":1,"notoc":true},"github":{"url":"https://github.com/apache/incub ator-hivemall/"},"splitter":{},"search":{},"downloadpdf":{"base":"https://github.com/apache/incubator-hivemall/docs/gitbook","label":"PDF","multilingual":false},"multipart":{},"localized-footer":{"filename":"FOOTER.md","hline":"true"},"lunr":{"maxIndexSize":1000000,"ignoreSpecialCharacters":false},"katex":{},"fontsettings":{"theme":"white","family":"sans","size":2,"font":"sans"},"highlight":{},"codeblock-filename":{},"sitemap":{"hostname":"http://hivemall.incubator.apache.org/"},"theme-api":{"languages":[],"split":false,"theme":"dark"},"sharing":{"facebook":true,"twitter":true,"google":false,"weibo":false,"instapaper":false,"vk":false,"all":["facebook","google","twitter","weibo","instapaper"]},"edit-link":{"label":"Edit","base":"https://github.com/apache/incubator-hivemall/docs/gitbook"},"theme-default":{"styles":{"website":"styles/website.css","pdf":"styles/pdf.css","epub":"styles/epub.css","mobi":"styles/mobi.css","ebook":"styles/ebook.css","print":"styles/print.css"},"showLevel": true},"anchorjs":{"selector":"h1,h2,h3,*:not(.callout) > h4,h5"},"toggle-chapters":{},"expandable-chapters":{}},"theme":"default","pdf":{"pageNumbers":true,"fontSize":12,"fontFamily":"Arial","paperSize":"a4","chapterMark":"pagebreak","pageBreaksBefore":"/","margin":{"right":62,"left":62,"top":56,"bottom":56}},"structure":{"langs":"LANGS.md","readme":"README.md","glossary":"GLOSSARY.md","summary":"SUMMARY.md"},"variables":{},"title":"Hivemall User Manual","links":{"sidebar":{"<i class=\"fa fa-home\"></i> Home":"http://hivemall.incubator.apache.org/"}},"gitbook":"3.x.x","description":"User Manual for Apache Hivemall"},"file":{"path":"binaryclass/kdd2010a.md","mtime":"2017-02-08T07:24:57.000Z","type":"markdown"},"gitbook":{"version":"3.2.2","time":"2017-06-15T10:33:21.138Z"},"basePath":"..","book":{"language":""}}); + gitbook.page.hasChanged({"page":{"title":"KDD2010a tutorial","level":"6.4","depth":1,"next":{"title":"Data preparation","level":"6.4.1","depth":2,"path":"binaryclass/kdd2010a_dataset.md","ref":"binaryclass/kdd2010a_dataset.md","articles":[]},"previous":{"title":"AdaGradRDA, AdaGrad, AdaDelta","level":"6.3.4","depth":2,"path":"binaryclass/news20_adagrad.md","ref":"binaryclass/news20_adagrad.md","articles":[]},"dir":"ltr"},"config":{"plugins":["theme-api","edit-link","github","splitter","sitemap","etoc","callouts","toggle-chapters","anchorjs","codeblock-filename","expandable-chapters","multipart","codeblock-filename","katex","emphasize","localized-footer"],"styles":{"website":"styles/website.css","pdf":"styles/pdf.css","epub":"styles/epub.css","mobi":"styles/mobi.css","ebook":"styles/ebook.css","print":"styles/print.css"},"pluginsConfig":{"emphasize":{},"callouts":{},"etoc":{"h2lb":3,"header":1,"maxdepth":3,"mindepth":1,"notoc":true},"github":{"url":"https://github.com/apa che/incubator-hivemall/"},"splitter":{},"search":{},"downloadpdf":{"base":"https://github.com/apache/incubator-hivemall/docs/gitbook","label":"PDF","multilingual":false},"multipart":{},"localized-footer":{"filename":"FOOTER.md","hline":"true"},"lunr":{"maxIndexSize":1000000,"ignoreSpecialCharacters":false},"katex":{},"fontsettings":{"theme":"white","family":"sans","size":2,"font":"sans"},"highlight":{},"codeblock-filename":{},"sitemap":{"hostname":"http://hivemall.incubator.apache.org/"},"theme-api":{"languages":[],"split":false,"theme":"dark"},"sharing":{"facebook":true,"twitter":true,"google":false,"weibo":false,"instapaper":false,"vk":false,"all":["facebook","google","twitter","weibo","instapaper"]},"edit-link":{"label":"Edit","base":"https://github.com/apache/incubator-hivemall/docs/gitbook"},"theme-default":{"styles":{"website":"styles/website.css","pdf":"styles/pdf.css","epub":"styles/epub.css","mobi":"styles/mobi.css","ebook":"styles/ebook.css","print":"styles/print.css"},"sh owLevel":true},"anchorjs":{"selector":"h1,h2,h3,*:not(.callout) > h4,h5"},"toggle-chapters":{},"expandable-chapters":{}},"theme":"default","pdf":{"pageNumbers":true,"fontSize":12,"fontFamily":"Arial","paperSize":"a4","chapterMark":"pagebreak","pageBreaksBefore":"/","margin":{"right":62,"left":62,"top":56,"bottom":56}},"structure":{"langs":"LANGS.md","readme":"README.md","glossary":"GLOSSARY.md","summary":"SUMMARY.md"},"variables":{},"title":"Hivemall User Manual","links":{"sidebar":{"<i class=\"fa fa-home\"></i> Home":"http://hivemall.incubator.apache.org/"}},"gitbook":"3.x.x","description":"User Manual for Apache Hivemall"},"file":{"path":"binaryclass/kdd2010a.md","mtime":"2016-12-02T08:02:42.000Z","type":"markdown"},"gitbook":{"version":"3.2.2","time":"2017-06-23T09:59:20.878Z"},"basePath":"..","book":{"language":""}}); }); </script> </div>
