{"id":1457,"date":"2025-01-27T07:04:55","date_gmt":"2025-01-27T07:04:55","guid":{"rendered":"https:\/\/mailitics.com\/index.php\/2025\/01\/27\/2501-14430\/"},"modified":"2025-01-27T07:04:55","modified_gmt":"2025-01-27T07:04:55","slug":"2501-14430","status":"publish","type":"post","link":"https:\/\/mailitics.com\/index.php\/2025\/01\/27\/2501-14430\/","title":{"rendered":"Statistical Verification of Linear Classifiers"},"content":{"rendered":"<p>    Statistical Verification of Linear Classifiers<br \/>\n \t<BR><br \/>\n<BR><\/BR><br \/>\n    <!-- no image --><br \/>\n \t<BR><br \/>\n<BR><\/BR><\/p>\n<div>arXiv:2501.14430v1 Announce Type: new<br \/>\nAbstract: We propose a homogeneity test closely related to the concept of linear separability between two samples. Using the test one can answer the question whether a linear classifier is merely &#8220;random&#8221; or effectively captures differences between two classes. We focus on establishing upper bounds for the test&#8217;s emph{p}-value when applied to two-dimensional samples. Specifically, for normally distributed samples we experimentally demonstrate that the upper bound is highly accurate. Using this bound, we evaluate classifiers designed to detect ER-positive breast cancer recurrence based on gene pair expression. Our findings confirm significance of IGFBP6 and ELOVL5 genes in this process.<\/div>\n<p> \t<BR><br \/>\n <BR><\/BR><br \/>\n    Anton Zhiyanov, Alexander Shklyaev, Alexey Galatenko, Vladimir Galatenko, Alexander Tonevitsky<br \/>\n \t<BR><br \/>\n<BR><\/BR><br \/>\n<a href=\"https:\/\/arxiv.org\/abs\/2501.14430\">Go to original source<\/a><br \/>\n \t<BR><br \/>\n <BR><\/BR><\/p>\n","protected":false},"excerpt":{"rendered":"<p>Statistical Verification of Linear Classifiers arXiv:2501.14430v1 Announce Type: new Abstract: We propose a homogeneity test closely related to the concept of linear separability between two samples. Using the test one can answer the question whether a linear classifier is merely &#8220;random&#8221; or effectively captures differences between two classes. We focus on establishing upper bounds for [&hellip;]<\/p>\n","protected":false},"author":2,"featured_media":0,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[62,113,420,190,181,112,191],"tags":[1488,496,1106],"class_list":["post-1457","post","type-post","status-publish","format-standard","hentry","category-aimldsaimlds","category-cs-lg","category-math-pr","category-math-st","category-stat-ap","category-stat-ml","category-stat-th","tag-classifiers","tag-linear","tag-test"],"_links":{"self":[{"href":"https:\/\/mailitics.com\/index.php\/wp-json\/wp\/v2\/posts\/1457"}],"collection":[{"href":"https:\/\/mailitics.com\/index.php\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/mailitics.com\/index.php\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/mailitics.com\/index.php\/wp-json\/wp\/v2\/users\/2"}],"replies":[{"embeddable":true,"href":"https:\/\/mailitics.com\/index.php\/wp-json\/wp\/v2\/comments?post=1457"}],"version-history":[{"count":0,"href":"https:\/\/mailitics.com\/index.php\/wp-json\/wp\/v2\/posts\/1457\/revisions"}],"wp:attachment":[{"href":"https:\/\/mailitics.com\/index.php\/wp-json\/wp\/v2\/media?parent=1457"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/mailitics.com\/index.php\/wp-json\/wp\/v2\/categories?post=1457"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/mailitics.com\/index.php\/wp-json\/wp\/v2\/tags?post=1457"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}