{"id":6014,"date":"2025-08-12T07:02:26","date_gmt":"2025-08-12T07:02:26","guid":{"rendered":"https:\/\/mailitics.com\/index.php\/2025\/08\/12\/estimating-from-no-data-deriving-a-continuous-score-from-categories\/"},"modified":"2025-08-12T07:02:26","modified_gmt":"2025-08-12T07:02:26","slug":"estimating-from-no-data-deriving-a-continuous-score-from-categories","status":"publish","type":"post","link":"https:\/\/mailitics.com\/index.php\/2025\/08\/12\/estimating-from-no-data-deriving-a-continuous-score-from-categories\/","title":{"rendered":"Estimating from No Data: Deriving a Continuous Score from Categories"},"content":{"rendered":"<p>    Estimating from No Data: Deriving a Continuous Score from Categories<br \/>\n \t<BR><br \/>\n<BR><\/BR><br \/>\n    <!-- no image --><br \/>\n \t<BR><br \/>\n<BR><\/BR><\/p>\n<div>\n<p>A walk-through of and the maths behind using low-capacity networks to acquire fine-grained scoring when only categorical labelling is available for training. We use it to predict the severity of an infection on a scale based on information on just rough outcomes in previous cases.<\/p>\n<p>The post <a href=\"https:\/\/towardsdatascience.com\/estimating-from-no-data-deriving-a-continuous-score-from-categories\/\">Estimating from No Data: Deriving a Continuous Score from Categories<\/a> appeared first on <a href=\"https:\/\/towardsdatascience.com\/\">Towards Data Science<\/a>.<\/p>\n<\/div>\n<p> \t<BR><br \/>\n <BR><\/BR><br \/>\n    Elod Pal Csirmaz<br \/>\n \t<BR><br \/>\n<BR><\/BR><br \/>\n<a href=\"https:\/\/towardsdatascience.com\/estimating-from-no-data-deriving-a-continuous-score-from-categories\/\">Go to original source<\/a><br \/>\n \t<BR><br \/>\n <BR><\/BR><\/p>\n","protected":false},"excerpt":{"rendered":"<p>Estimating from No Data: Deriving a Continuous Score from Categories A walk-through of and the maths behind using low-capacity networks to acquire fine-grained scoring when only categorical labelling is available for training. We use it to predict the severity of an infection on a scale based on information on just rough outcomes in previous cases. [&hellip;]<\/p>\n","protected":false},"author":2,"featured_media":0,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[62,2770,83,240,1428,3489,803,70,3385,1780,157],"tags":[84,1215,1269],"class_list":["post-6014","post","type-post","status-publish","format-standard","hentry","category-aimldsaimlds","category-algebra","category-data-science","category-editors-pick","category-health","category-keras","category-linear-regression","category-machine-learning","category-medicine","category-neural-network","category-python","tag-data","tag-estimating","tag-no"],"_links":{"self":[{"href":"https:\/\/mailitics.com\/index.php\/wp-json\/wp\/v2\/posts\/6014"}],"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=6014"}],"version-history":[{"count":0,"href":"https:\/\/mailitics.com\/index.php\/wp-json\/wp\/v2\/posts\/6014\/revisions"}],"wp:attachment":[{"href":"https:\/\/mailitics.com\/index.php\/wp-json\/wp\/v2\/media?parent=6014"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/mailitics.com\/index.php\/wp-json\/wp\/v2\/categories?post=6014"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/mailitics.com\/index.php\/wp-json\/wp\/v2\/tags?post=6014"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}