{"id":2119,"date":"2017-07-15T11:35:20","date_gmt":"2017-07-15T09:35:20","guid":{"rendered":"https:\/\/ssad.statistics.sk\/SSaD\/index.php\/decision-trees-as-a-predictive-modeling-method\/"},"modified":"2020-01-17T13:59:30","modified_gmt":"2020-01-17T12:59:30","slug":"decision-trees-as-a-predictive-modeling-method","status":"publish","type":"post","link":"https:\/\/ssad.statistics.sk\/SSaD\/index.php\/decision-trees-as-a-predictive-modeling-method\/?lang=en","title":{"rendered":"Decision trees as a predictive modeling method"},"content":{"rendered":"<p>Viera Labudov\u00e1, Faculty of Economic Informatics, University of Economics in Bratislava, Slovak Republic<\/p>\n<p><!--more--><\/p>\n<p>Pages: 60 &#8211; 76<\/p>\n<h5>Abstract<\/h5>\n<p>Decision trees are powerful tools for classification and prediction. The attractiveness of tree-based methods is largely due to the fact that decision trees represent rules. When a decision tree is used for classification tasks (the target variable is categorical), it is referred to as a classification tree. When it is used for regression tasks (the target variable is continuous), it is called a regression tree. This article describes the structure of decision trees and the basic algorithm for their construction.<\/p>\n<div>\n<p><span style=\"line-height: 2.1em; padding-left: 0px; color: #1e4e9d;\">Issue for download<\/span><br \/>\n<a class=\"download-pdf\" onclick=\"window.open('https:\/\/ssad.statistics.sk\/SSaD\/?dl_id=230','new','');return false\"  href=\"https:\/\/ssad.statistics.sk\/SSaD\/?dl_id=230\"><i class=\"far fa-file-pdf\"><\/i> PDF<\/a><span class='download-text'> (1,5 MB, 1&nbsp;570 downloads)<\/p>\n<\/div>\n","protected":false},"excerpt":{"rendered":"<p>Viera Labudov\u00e1, Faculty of Economic Informatics, University of Economics in Bratislava, Slovak Republic<\/p>\n","protected":false},"author":4,"featured_media":0,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"_exactmetrics_skip_tracking":false,"_exactmetrics_sitenote_active":false,"_exactmetrics_sitenote_note":"","_exactmetrics_sitenote_category":0,"footnotes":""},"categories":[807],"tags":[975,979,976,977,978],"class_list":["post-2119","post","type-post","status-publish","format-standard","hentry","category-3-2017-scientific-articles","tag-author-viera-labudova","tag-decision-tree-algorithms-1-uvod","tag-decision-trees","tag-entropy","tag-gini-index"],"_links":{"self":[{"href":"https:\/\/ssad.statistics.sk\/SSaD\/index.php\/wp-json\/wp\/v2\/posts\/2119","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/ssad.statistics.sk\/SSaD\/index.php\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/ssad.statistics.sk\/SSaD\/index.php\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/ssad.statistics.sk\/SSaD\/index.php\/wp-json\/wp\/v2\/users\/4"}],"replies":[{"embeddable":true,"href":"https:\/\/ssad.statistics.sk\/SSaD\/index.php\/wp-json\/wp\/v2\/comments?post=2119"}],"version-history":[{"count":1,"href":"https:\/\/ssad.statistics.sk\/SSaD\/index.php\/wp-json\/wp\/v2\/posts\/2119\/revisions"}],"predecessor-version":[{"id":2120,"href":"https:\/\/ssad.statistics.sk\/SSaD\/index.php\/wp-json\/wp\/v2\/posts\/2119\/revisions\/2120"}],"wp:attachment":[{"href":"https:\/\/ssad.statistics.sk\/SSaD\/index.php\/wp-json\/wp\/v2\/media?parent=2119"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/ssad.statistics.sk\/SSaD\/index.php\/wp-json\/wp\/v2\/categories?post=2119"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/ssad.statistics.sk\/SSaD\/index.php\/wp-json\/wp\/v2\/tags?post=2119"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}