{"id":2705,"date":"2013-11-25T13:21:56","date_gmt":"2013-11-25T13:21:56","guid":{"rendered":"http:\/\/www.predictiveanalyticsworld.com\/machinelearningtimes\/?p=2705"},"modified":"2013-11-25T13:21:56","modified_gmt":"2013-11-25T13:21:56","slug":"selecting-mathematical-models-with-greatest-predictive-power-finding-occams-razor-in-an-era-of-information-overload","status":"publish","type":"post","link":"https:\/\/www.predictiveanalyticsworld.com\/machinelearningtimes\/selecting-mathematical-models-with-greatest-predictive-power-finding-occams-razor-in-an-era-of-information-overload\/2705\/","title":{"rendered":"Selecting Mathematical Models With Greatest Predictive Power: Finding Occam&#8217;s Razor in an Era of Information Overload"},"content":{"rendered":"How can the actions and reactions of proteins so small or stars so distant they are invisible to the human eye be accurately predicted? How can blurry images be brought into focus and reconstructed? A new study led by physicist Steve Press\u00e9, Ph.D., of the School of Science at Indiana University-Purdue University Indianapolis, shows that there may be a preferred strategy for selecting mathematical models with the greatest predictive power. Picking the best model is about sticking to the simplest line of reasoning, according to Press\u00e9. His paper explaining his theory is published online this month in Physical <a href=\"https:\/\/www.predictiveanalyticsworld.com\/machinelearningtimes\/selecting-mathematical-models-with-greatest-predictive-power-finding-occams-razor-in-an-era-of-information-overload\/2705\/\" class=\"more-link\">(more&hellip;)<\/a>","protected":false},"excerpt":{"rendered":"<p>How can the actions and reactions of proteins so small or stars so distant they are invisible to the human eye be accurately predicted? How can blurry images be brought into focus and reconstructed? A new study led by physicist Steve Press\u00e9, Ph.D., of the School of Science at Indiana University-Purdue University Indianapolis, shows that [&hellip;]<\/p>\n","protected":false},"author":2,"featured_media":0,"comment_status":"open","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"footnotes":"","_links_to":"","_links_to_target":""},"categories":[11],"tags":[226,110],"class_list":["post-2705","post","type-post","status-publish","format-standard","hentry","category-industry-news","tag-indiana-university-purdue-university","tag-prediction"],"_links":{"self":[{"href":"https:\/\/www.predictiveanalyticsworld.com\/machinelearningtimes\/wp-json\/wp\/v2\/posts\/2705","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.predictiveanalyticsworld.com\/machinelearningtimes\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.predictiveanalyticsworld.com\/machinelearningtimes\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.predictiveanalyticsworld.com\/machinelearningtimes\/wp-json\/wp\/v2\/users\/2"}],"replies":[{"embeddable":true,"href":"https:\/\/www.predictiveanalyticsworld.com\/machinelearningtimes\/wp-json\/wp\/v2\/comments?post=2705"}],"version-history":[{"count":2,"href":"https:\/\/www.predictiveanalyticsworld.com\/machinelearningtimes\/wp-json\/wp\/v2\/posts\/2705\/revisions"}],"predecessor-version":[{"id":2707,"href":"https:\/\/www.predictiveanalyticsworld.com\/machinelearningtimes\/wp-json\/wp\/v2\/posts\/2705\/revisions\/2707"}],"wp:attachment":[{"href":"https:\/\/www.predictiveanalyticsworld.com\/machinelearningtimes\/wp-json\/wp\/v2\/media?parent=2705"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.predictiveanalyticsworld.com\/machinelearningtimes\/wp-json\/wp\/v2\/categories?post=2705"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.predictiveanalyticsworld.com\/machinelearningtimes\/wp-json\/wp\/v2\/tags?post=2705"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}