{"id":2165,"date":"2021-11-22T13:40:39","date_gmt":"2021-11-22T13:40:39","guid":{"rendered":"http:\/\/optimumsportsperformance.com\/blog\/?p=2165"},"modified":"2021-11-22T13:40:39","modified_gmt":"2021-11-22T13:40:39","slug":"tidyx-84-workflowsets-in-tidymodels","status":"publish","type":"post","link":"https:\/\/optimumsportsperformance.com\/blog\/tidyx-84-workflowsets-in-tidymodels\/","title":{"rendered":"TidyX 84: Workflowsets in tidymodels"},"content":{"rendered":"<p>We&#8217;ve been working on developing machine learning models using {<strong>tidymodels<\/strong>} over the past several weeks. Sometimes, though, you need to build a variety of models on your data. This week, <span style=\"color: #0000ff;\"><strong><a style=\"color: #0000ff;\" href=\"https:\/\/twitter.com\/ellis_hughes\">Ellis Hughes<\/a><\/strong><\/span> and I explore {<strong>workflowsets<\/strong>}.<\/p>\n<p>Workflow sets allow you to set specific recipes for different model types and then run a variety of models simultaneously. Topics we cover:<\/p>\n<ul>\n<li>Setting up recipes<\/li>\n<li>Specifying multiple models<\/li>\n<li>Creating a workflowset<\/li>\n<li>Fitting all models within the workflowset<\/li>\n<li>Choosing the optimal model<\/li>\n<li>Two different approaches to fitting the optimal model on your test data set<\/li>\n<\/ul>\n<p>To watch our screen cast, <strong><span style=\"color: #0000ff;\"><a style=\"color: #0000ff;\" href=\"https:\/\/www.youtube.com\/watch?v=YZqbOATpjM4\">CLICK HERE<\/a><\/span><\/strong>.<\/p>\n<p>To access the code and data (courtesy of kaggle), <strong><span style=\"color: #0000ff;\"><a style=\"color: #0000ff;\" href=\"https:\/\/github.com\/thebioengineer\/TidyX\/tree\/master\/TidyTuesday_Explained\/084-Tidy_Models_8\">CLICK HERE<\/a><\/span><\/strong>.<\/p>\n<p>If you like what we are doing and would like to buy us a coffee or beer, visit our Patreon page <strong><span style=\"color: #0000ff;\">HERE<\/span><\/strong>.<\/p>\n","protected":false},"excerpt":{"rendered":"<p>We&#8217;ve been working on developing machine learning models using {tidymodels} over the past several weeks. Sometimes, though, you need to build a variety of models on your data. This week, Ellis Hughes and I explore {workflowsets}. Workflow sets allow you to set specific recipes for different model types and then run a variety of models [&hellip;]<\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[44],"tags":[],"class_list":["post-2165","post","type-post","status-publish","format-standard","hentry","category-tidyx-screen-cast"],"_links":{"self":[{"href":"https:\/\/optimumsportsperformance.com\/blog\/wp-json\/wp\/v2\/posts\/2165","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/optimumsportsperformance.com\/blog\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/optimumsportsperformance.com\/blog\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/optimumsportsperformance.com\/blog\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/optimumsportsperformance.com\/blog\/wp-json\/wp\/v2\/comments?post=2165"}],"version-history":[{"count":1,"href":"https:\/\/optimumsportsperformance.com\/blog\/wp-json\/wp\/v2\/posts\/2165\/revisions"}],"predecessor-version":[{"id":2166,"href":"https:\/\/optimumsportsperformance.com\/blog\/wp-json\/wp\/v2\/posts\/2165\/revisions\/2166"}],"wp:attachment":[{"href":"https:\/\/optimumsportsperformance.com\/blog\/wp-json\/wp\/v2\/media?parent=2165"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/optimumsportsperformance.com\/blog\/wp-json\/wp\/v2\/categories?post=2165"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/optimumsportsperformance.com\/blog\/wp-json\/wp\/v2\/tags?post=2165"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}