{"id":464,"date":"2024-12-10T07:01:00","date_gmt":"2024-12-10T07:01:00","guid":{"rendered":"https:\/\/mailitics.com\/index.php\/2024\/12\/10\/uncertainty-quantification-in-time-series-forecasting-c9599d15b08b\/"},"modified":"2024-12-10T07:01:00","modified_gmt":"2024-12-10T07:01:00","slug":"uncertainty-quantification-in-time-series-forecasting-c9599d15b08b","status":"publish","type":"post","link":"https:\/\/mailitics.com\/index.php\/2024\/12\/10\/uncertainty-quantification-in-time-series-forecasting-c9599d15b08b\/","title":{"rendered":"Uncertainty Quantification in Time Series Forecasting"},"content":{"rendered":"<p>    Uncertainty Quantification in Time Series Forecasting<br \/>\n \t<BR><br \/>\n<BR><\/BR><br \/>\n    <!-- no image --><br \/>\n \t<BR><br \/>\n<BR><\/BR><\/p>\n<div>\n<div class=\"medium-feed-item\">\n<p class=\"medium-feed-image\"><a href=\"https:\/\/towardsdatascience.com\/uncertainty-quantification-in-time-series-forecasting-c9599d15b08b\"><img data-recalc-dims=\"1\" decoding=\"async\" src=\"https:\/\/i0.wp.com\/cdn-images-1.medium.com\/max\/1536\/1%2AUIAPWbgPWsfz1EPESWp9mA.png?w=1536&#038;ssl=1\" ><\/a><\/p>\n<p class=\"medium-feed-snippet\">A deep dive into EnbPI, a Conformal Prediction approach for time series forecasting<\/p>\n<p class=\"medium-feed-link\"><a href=\"https:\/\/towardsdatascience.com\/uncertainty-quantification-in-time-series-forecasting-c9599d15b08b\">Continue reading on Towards Data Science \u00bb<\/a><\/p>\n<\/div>\n<\/div>\n<p> \t<BR><br \/>\n <BR><\/BR><br \/>\n    Jonte Dancker<br \/>\n \t<BR><br \/>\n<BR><\/BR><br \/>\n<a href=\"https:\/\/medium.com\/m\/global-identity-2?redirectUrl=https%3A%2F%2Ftowardsdatascience.com%2Funcertainty-quantification-in-time-series-forecasting-c9599d15b08b\">Go to original source<\/a><br \/>\n \t<BR><br \/>\n <BR><\/BR><\/p>\n","protected":false},"excerpt":{"rendered":"<p>Uncertainty Quantification in Time Series Forecasting A deep dive into EnbPI, a Conformal Prediction approach for time series forecasting Continue reading on Towards Data Science \u00bb Jonte Dancker Go to original source<\/p>\n","protected":false},"author":2,"featured_media":0,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[62,573,83,166,70,353],"tags":[355,325,15],"class_list":["post-464","post","type-post","status-publish","format-standard","hentry","category-aimldsaimlds","category-conformal-prediction","category-data-science","category-hands-on-tutorials","category-machine-learning","category-time-series-forecasting","tag-forecasting","tag-series","tag-time"],"_links":{"self":[{"href":"https:\/\/mailitics.com\/index.php\/wp-json\/wp\/v2\/posts\/464"}],"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=464"}],"version-history":[{"count":0,"href":"https:\/\/mailitics.com\/index.php\/wp-json\/wp\/v2\/posts\/464\/revisions"}],"wp:attachment":[{"href":"https:\/\/mailitics.com\/index.php\/wp-json\/wp\/v2\/media?parent=464"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/mailitics.com\/index.php\/wp-json\/wp\/v2\/categories?post=464"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/mailitics.com\/index.php\/wp-json\/wp\/v2\/tags?post=464"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}