{"id":41331,"date":"2024-10-30T19:56:51","date_gmt":"2024-10-31T00:56:51","guid":{"rendered":"https:\/\/huewhite.com\/umb\/?p=41331"},"modified":"2024-10-30T19:56:51","modified_gmt":"2024-10-31T00:56:51","slug":"word-of-the-day-999","status":"publish","type":"post","link":"https:\/\/huewhite.com\/umb\/2024\/10\/30\/word-of-the-day-999\/","title":{"rendered":"Word Of The Day"},"content":{"rendered":"

Markov blanket<\/em>:<\/p>\n

In\u00a0statistics<\/a>\u00a0and\u00a0machine learning<\/a>, when one wants to infer a random variable with a set of variables, usually a subset is enough, and other variables are useless. Such a subset that contains all the useful information is called a\u00a0Markov blanket<\/b>. If a Markov blanket is minimal, meaning that it cannot drop any variable without losing information, it is called a\u00a0Markov boundary<\/b>. Identifying a Markov blanket or a Markov boundary helps to extract useful features. The terms of Markov blanket and Markov boundary were coined by\u00a0Judea Pearl<\/a> in 1988.\u00a0A Markov blanket can be constituted by a set of\u00a0Markov chains<\/a>. [Wikipedia<\/strong><\/a>]<\/em><\/p><\/blockquote>\n

Noted in “The free-energy principle: Can one idea explain why everything exists?<\/em><\/a>” Elise Cutts, NewScientist<\/strong><\/em> (19 October 2024, paywall):<\/p>\n

To divide the brain from the world it models, Friston implemented another mathematical tool: the Markov blanket. This acts as a sort of causal go-between, determining the relevant information that defines a particular brain state …. Depending on the scale you are interested in, a brain state could be something as granular as whether a particular neuron is firing or as enormous as depression.<\/p><\/blockquote>\n

Hmmmmmmm. I seem to remember something about Markov chains, which is part of this concept, when I was messing about on Kaggle<\/strong><\/em><\/a>. Don’t bother to ask, I wasn’t any good at it.<\/p>\n","protected":false},"excerpt":{"rendered":"

Markov blanket: In\u00a0statistics\u00a0and\u00a0machine learning, when one wants to infer a random variable with a set of variables, usually a subset is enough, and other variables are useless. Such a subset that contains all the useful information is called a\u00a0Markov blanket. If a Markov blanket is minimal, meaning that it cannot \u2026 Continue reading → <\/span><\/a><\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"nf_dc_page":"","_jetpack_memberships_contains_paid_content":false,"footnotes":""},"categories":[1],"tags":[],"class_list":["post-41331","post","type-post","status-publish","format-standard","hentry","category-uncategorized"],"jetpack_featured_media_url":"","jetpack_sharing_enabled":true,"_links":{"self":[{"href":"https:\/\/huewhite.com\/umb\/wp-json\/wp\/v2\/posts\/41331","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/huewhite.com\/umb\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/huewhite.com\/umb\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/huewhite.com\/umb\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/huewhite.com\/umb\/wp-json\/wp\/v2\/comments?post=41331"}],"version-history":[{"count":1,"href":"https:\/\/huewhite.com\/umb\/wp-json\/wp\/v2\/posts\/41331\/revisions"}],"predecessor-version":[{"id":41332,"href":"https:\/\/huewhite.com\/umb\/wp-json\/wp\/v2\/posts\/41331\/revisions\/41332"}],"wp:attachment":[{"href":"https:\/\/huewhite.com\/umb\/wp-json\/wp\/v2\/media?parent=41331"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/huewhite.com\/umb\/wp-json\/wp\/v2\/categories?post=41331"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/huewhite.com\/umb\/wp-json\/wp\/v2\/tags?post=41331"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}