--- title: What Is Recall? | daily.dev description: Recall is a model evaluation metric that measures how many real objects a model successfully detects, calculated as TP / (TP + FN). A high Recall means fewer... canonical: https://daily.dev/posts/what-is-recall--zy9dqjyni twitter:card: summary_large_image twitter:site: @dailydotdev og:type: website og:site_name: daily.dev og:title: What Is Recall? | daily.dev og:description: Recall is a model evaluation metric that measures how many real objects a model successfully detects, calculated as TP / (TP + FN). A high Recall means fewer... og:url: https://daily.dev/posts/what-is-recall--zy9dqjyni og:image: https://api.daily.dev/og/posts/ZY9dqJYNI.png og:image:alt: What Is Recall? 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. # What Is Recall? **[Medium](https://daily.dev/sources/medium_js)** · 5 min read · 0 upvotes · 0 comments ## Summary Recall is a model evaluation metric that measures how many real objects a model successfully detects, calculated as TP / (TP + FN). A high Recall means fewer missed detections, but increasing Recall can reduce Precision. The post explains True Positives and False Negatives, walks through a worked example with medicine box detection, and discusses when Recall matters most (e.g., medical diagnosis vs. spam filtering). It also covers strategies to improve Recall such as diversifying training data, fixing annotations, and tuning confidence thresholds. ## Full article daily.dev links to this article rather than hosting it. Read it at the original source: ## Similar posts on daily.dev - [What Is Precision?](https://daily.dev/posts/what-is-precision--js5ycsds0) · Medium · 0 upvotes · 0 comments - [Beyond Accuracy: Why Precision and Recall Matter More Than You Think](https://daily.dev/posts/beyond-accuracy-why-precision-and-recall-matter-more-than-you-think-rnacoqd5w) · BigData Boutique blog · 3 upvotes · 0 comments - [Machine Learning Model Evaluation: How Do We Know Our Model Is Good?](https://daily.dev/posts/machine-learning-model-evaluation-how-do-we-know-our-model-is-good--qekvejzgn) · Medium · 0 upvotes · 0 comments - [How to Evaluate an ML Model Performance?](https://daily.dev/posts/how-to-evaluate-an-ml-model-performance--xmijfsj9t) · Serokell · 0 upvotes · 0 comments - [The Machine Learning “Advent Calendar” Bonus 1: AUC in Excel](https://daily.dev/posts/the-machine-learning-advent-calendar-bonus-1-auc-in-excel-ueqhez6w5) · Towards Data Science · 1 upvotes · 0 comments --- Tags: [#machine-learning](https://daily.dev/tags/machine-learning), [#data-science](https://daily.dev/tags/data-science), [#object-detection](https://daily.dev/tags/object-detection) [View this post on daily.dev](https://daily.dev/posts/what-is-recall--zy9dqjyni) ```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":"What Is Recall?","url":"https://daily.dev/posts/what-is-recall--zy9dqjyni","mainEntityOfPage":{"@type":"WebPage","@id":"https://daily.dev/posts/what-is-recall--zy9dqjyni"},"datePublished":"2026-07-21T09:29:26.755Z","dateModified":"2026-07-21T09:32:14.694Z","description":"Recall is a model evaluation metric that measures how many real objects a model successfully detects, calculated as TP / (TP + FN). 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