{"id":1254,"date":"2026-01-25T19:33:50","date_gmt":"2026-01-25T19:33:50","guid":{"rendered":"https:\/\/www.cs.ubbcluj.ro\/~meco\/log-loss-optimization-for-boosting-a-nash-equilibrium-decision-tree-2025\/"},"modified":"2026-02-01T12:07:26","modified_gmt":"2026-02-01T12:07:26","slug":"log-loss-optimization-for-boosting-a-nash-equilibrium-decision-tree-2025","status":"publish","type":"post","link":"https:\/\/www.cs.ubbcluj.ro\/~meco\/log-loss-optimization-for-boosting-a-nash-equilibrium-decision-tree-2025\/","title":{"rendered":"Log-Loss Optimization for Boosting a Nash Equilibrium Decision Tree (2025)"},"content":{"rendered":"<div class=\"entry-content\">\n<p>Cybernetics and systems<\/p>\n<h2>Authors<\/h2>\n<p>R. Lung, M. Suciu<\/p>\n<h2>Abstract<\/h2>\n<p>Decision trees rank among the most popular classification tools, employed in practical applications due to their known efficiency. A Nash equilibrium-based decision tree splits node data using the Nash equilibrium concept. Boosting is a technique that is used to enhance the performance of a classifier by allowing an in-depth exploration of the data. This paper proposes the use of an AdaBoost model with a log-loss optimization mechanism to improve the performance of an equilibrium-based decision tree. The two-step approach first builds equilibrium decision trees on weighted data; after that, determines the contribution of each classifier by optimizing the overall log-loss function. Numerical experiments illustrate the approach\u2019s performance by comparing results on a set of synthetic and real-world data with state-of-the-art tree-based boosting methods.<\/p>\n<h2>Citation<\/h2>\n<pre class=\"wp-block-preformatted\">@Inproceedings{Lung2025LogLossOF,\n author = {R. Lung and M. Suciu},\n booktitle = {Cybernetics and systems},\n title = {Log-Loss Optimization for Boosting a Nash Equilibrium Decision Tree},\n year = {2025}\n}<\/pre>\n<\/div>\n","protected":false},"excerpt":{"rendered":"<p>Decision trees rank among the most popular classification tools, employed in practical applications due to their known efficiency. A Nash equilibrium-based decision tree splits node data using the Nash equilibrium concept. Boosting is a technique that is used to enhance the performance of a classifier by allowing an in-depth exploration of the data. This paper proposes the use of an AdaBoost model with a log-loss optimization mechanism to improve the performance of an equilibrium-based decision tree. The two-step approach first builds equilibrium decision trees on weighted data; after that, determines the contribution of each classifier by optimizing the overall log-loss function. Numerical experiments illustrate the approach\u2019s performance by comparing results on a set of synthetic and real-world data with state-of-the-art tree-based boosting methods.<\/p>\n","protected":false},"author":6,"featured_media":1037,"comment_status":"closed","ping_status":"","sticky":false,"template":"","format":"standard","meta":[],"categories":[4],"tags":[11,35,20],"_links":{"self":[{"href":"https:\/\/www.cs.ubbcluj.ro\/~meco\/wp-json\/wp\/v2\/posts\/1254"}],"collection":[{"href":"https:\/\/www.cs.ubbcluj.ro\/~meco\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.cs.ubbcluj.ro\/~meco\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.cs.ubbcluj.ro\/~meco\/wp-json\/wp\/v2\/users\/6"}],"replies":[{"embeddable":true,"href":"https:\/\/www.cs.ubbcluj.ro\/~meco\/wp-json\/wp\/v2\/comments?post=1254"}],"version-history":[{"count":2,"href":"https:\/\/www.cs.ubbcluj.ro\/~meco\/wp-json\/wp\/v2\/posts\/1254\/revisions"}],"predecessor-version":[{"id":1427,"href":"https:\/\/www.cs.ubbcluj.ro\/~meco\/wp-json\/wp\/v2\/posts\/1254\/revisions\/1427"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/www.cs.ubbcluj.ro\/~meco\/wp-json\/wp\/v2\/media\/1037"}],"wp:attachment":[{"href":"https:\/\/www.cs.ubbcluj.ro\/~meco\/wp-json\/wp\/v2\/media?parent=1254"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.cs.ubbcluj.ro\/~meco\/wp-json\/wp\/v2\/categories?post=1254"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.cs.ubbcluj.ro\/~meco\/wp-json\/wp\/v2\/tags?post=1254"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}