{"id":10,"date":"2005-01-31T08:07:11","date_gmt":"2005-01-31T14:07:11","guid":{"rendered":"\/?p=10"},"modified":"2005-02-04T09:45:39","modified_gmt":"2005-02-04T15:45:39","slug":"watchword-assumption","status":"publish","type":"post","link":"https:\/\/hunch.net\/?p=10","title":{"rendered":"Watchword: Assumption"},"content":{"rendered":"<p>&#8220;Assumption&#8221; is another word to be careful with in machine learning because it is used in several ways.<\/p>\n<ol>\n<li><strong>Assumption = Bias<\/strong> There are several ways to see that some form of &#8216;bias&#8217; (= preferring of one solution over another) is necessary.   This is obvious in an adversarial setting.  A good bit of work has been expended explaining this in other settings with &#8220;<a href=\"http:\/\/www.no-free-lunch.org\/\">no free lunch<\/a>&#8221; theorems.  This is a usage specialized to learning which is particularly common when talking about priors for Bayesian Learning.<\/li>\n<li><strong>Assumption = &#8220;if&#8221; of a theorem<\/strong> The assumptions are the &#8216;if&#8217; part of the &#8216;if-then&#8217; in a theorem.  This is a fairly common usage.<\/li>\n<li><strong>Assumption = Axiom<\/strong> The assumptions are the things that we assume are true, but which we cannot verify.  Examples are &#8220;the IID assumption&#8221; or &#8220;my problem is a DNF on a small number of bits&#8221;.  This is the usage which I prefer.<\/li>\n<\/ol>\n<p>One difficulty with any use of the word &#8220;assumption&#8221; is that you often encounter &#8220;if <em>assumption<\/em> then <em>conclusion<\/em> so if <em>not assumption<\/em> then <em>not conclusion<\/em>&#8220;.  This is incorrect logic.  For example, with variant (1), &#8220;the assumption of my prior is not met so the algorithm will not learn&#8221;.  Or, with variant (3), &#8220;the data is not IID, so my learning algorithm designed for IID data will not work&#8221;.  In each of these cases &#8220;will&#8221; must be replaced with &#8220;may&#8221; for correctness.<\/p>\n","protected":false},"excerpt":{"rendered":"<p>&#8220;Assumption&#8221; is another word to be careful with in machine learning because it is used in several ways. Assumption = Bias There are several ways to see that some form of &#8216;bias&#8217; (= preferring of one solution over another) is necessary. This is obvious in an adversarial setting. A good bit of work has been &hellip; <\/p>\n<p class=\"link-more\"><a href=\"https:\/\/hunch.net\/?p=10\" class=\"more-link\">Continue reading<span class=\"screen-reader-text\"> &#8220;Watchword: Assumption&#8221;<\/span><\/a><\/p>\n","protected":false},"author":2,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[15],"tags":[],"class_list":["post-10","post","type-post","status-publish","format-standard","hentry","category-definitions"],"_links":{"self":[{"href":"https:\/\/hunch.net\/index.php?rest_route=\/wp\/v2\/posts\/10","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/hunch.net\/index.php?rest_route=\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/hunch.net\/index.php?rest_route=\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/hunch.net\/index.php?rest_route=\/wp\/v2\/users\/2"}],"replies":[{"embeddable":true,"href":"https:\/\/hunch.net\/index.php?rest_route=%2Fwp%2Fv2%2Fcomments&post=10"}],"version-history":[{"count":0,"href":"https:\/\/hunch.net\/index.php?rest_route=\/wp\/v2\/posts\/10\/revisions"}],"wp:attachment":[{"href":"https:\/\/hunch.net\/index.php?rest_route=%2Fwp%2Fv2%2Fmedia&parent=10"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/hunch.net\/index.php?rest_route=%2Fwp%2Fv2%2Fcategories&post=10"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/hunch.net\/index.php?rest_route=%2Fwp%2Fv2%2Ftags&post=10"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}