--- title: Utilizing target permutation to prevent overfitting. description: The author describes a method to assess whether the results of a model are random or statistically significant by permuting the target vector in the training... canonical: https://daily.dev/posts/utilizing-target-permutation-to-prevent-overfitting--60nw7ihy8 twitter:card: summary_large_image twitter:site: @dailydotdev og:type: website og:site_name: daily.dev og:title: Utilizing target permutation to prevent overfitting. | daily.dev og:description: The author describes a method to assess whether the results of a model are random or statistically significant by permuting the target vector in the training... og:url: https://daily.dev/posts/utilizing-target-permutation-to-prevent-overfitting--60nw7ihy8 og:image: https://api.daily.dev/og/posts/60NW7ihY8.png og:image:alt: Utilizing target permutation to prevent overfitting. og:image:width: 1200 og:image:height: 630 og:locale: en --- > ## Documentation Index > Fetch the complete documentation index at: https://daily.dev/llms.txt > Use this file to discover all available pages before exploring further. # Utilizing target permutation to prevent overfitting. **[Medium](https://daily.dev/sources/medium_js)** · 4 min read · 0 upvotes · 0 comments ## Summary The author describes a method to assess whether the results of a model are random or statistically significant by permuting the target vector in the training set and evaluating the results on the original target in the test set. The results showed that the non-permuted target vector outperformed most randomly permuted vectors, but there were instances where the model trained better with a randomly permuted vector. ## Full article daily.dev links to this article rather than hosting it. Read it at the original source: --- Tags: [#ai](https://daily.dev/tags/ai), [#data-science](https://daily.dev/tags/data-science), [#machine-learning](https://daily.dev/tags/machine-learning), [#feature-engineering](https://daily.dev/tags/feature-engineering), [#overfitting](https://daily.dev/tags/overfitting) [View this post on daily.dev](https://daily.dev/posts/utilizing-target-permutation-to-prevent-overfitting--60nw7ihy8) ```json {"@context":"https://schema.org","@graph":[{"@type":"Organization","@id":"https://daily.dev/#organization","name":"daily.dev","url":"https://daily.dev","logo":{"@type":"ImageObject","url":"https://daily.dev/apple-touch-icon.png","width":180,"height":180},"sameAs":["https://twitter.com/dailydotdev","https://github.com/dailydotdev","https://www.linkedin.com/company/daily-dev-ltd"]},{"@type":"WebSite","@id":"https://daily.dev/#website","url":"https://daily.dev","name":"daily.dev","publisher":{"@id":"https://daily.dev/#organization"},"potentialAction":{"@type":"SearchAction","target":{"@type":"EntryPoint","urlTemplate":"https://daily.dev/search?q={search_term_string}"},"query-input":"required name=search_term_string"}}]} {"@context":"https://schema.org","@type":"TechArticle","headline":"Utilizing target permutation to prevent overfitting.","url":"https://daily.dev/posts/utilizing-target-permutation-to-prevent-overfitting--60nw7ihy8","mainEntityOfPage":{"@type":"WebPage","@id":"https://daily.dev/posts/utilizing-target-permutation-to-prevent-overfitting--60nw7ihy8"},"datePublished":"2024-01-09T12:11:36.858Z","dateModified":"2024-01-09T12:11:35.863Z","description":"The author describes a method to assess whether the results of a model are random or statistically significant by permuting the target vector in the training...","image":"https://media.daily.dev/image/upload/f_auto,q_auto/v1/posts/e9008b1ea858e98332555b01db05f9e9?_a=AQAEufR","thumbnailUrl":"https://media.daily.dev/image/upload/f_auto,q_auto/v1/posts/e9008b1ea858e98332555b01db05f9e9?_a=AQAEufR","isAccessibleForFree":true,"articleSection":"Medium","inLanguage":"en","publisher":{"@type":"Organization","name":"daily.dev","url":"https://daily.dev","logo":{"@type":"ImageObject","url":"https://daily.dev/apple-touch-icon.png","width":180,"height":180}},"author":{"@type":"Organization","name":"Medium","logo":"https://media.daily.dev/image/upload/t_logo,f_auto/v1/logos/medium","url":"https://daily.dev/sources/medium_js"},"commentCount":0,"discussionUrl":"https://daily.dev/posts/utilizing-target-permutation-to-prevent-overfitting--60nw7ihy8","interactionStatistic":[{"@type":"InteractionCounter","interactionType":{"@type":"LikeAction"},"userInteractionCount":0},{"@type":"InteractionCounter","interactionType":{"@type":"CommentAction"},"userInteractionCount":0}],"keywords":"ai,data-science,machine-learning,feature-engineering,overfitting","timeRequired":"PT4M"} {"@context":"https://schema.org","@type":"BreadcrumbList","itemListElement":[{"@type":"ListItem","position":1,"name":"Home","item":"https://daily.dev"},{"@type":"ListItem","position":2,"name":"Medium","item":"https://daily.dev/sources/medium_js"},{"@type":"ListItem","position":3,"name":"Utilizing target permutation to prevent overfitting."}]} ```