{"id":24379,"date":"2026-10-17T16:19:37","date_gmt":"2026-10-17T14:19:37","guid":{"rendered":"https:\/\/www.neuraldesigner.com\/learning\/tutorials\/text-classification-model\/"},"modified":"2026-10-17T16:19:37","modified_gmt":"2026-10-17T14:19:37","slug":"text-classification-model","status":"publish","type":"learning","link":"https:\/\/www.neuraldesigner.com\/learning\/tutorials\/text-classification-model\/","title":{"rendered":"Model types: Text classification"},"content":{"rendered":"<style id=\"nd-tutorial-series-css\">.ndts{max-width:1000px;margin:0 auto 26px;padding:18px 20px;border:1px solid #d8e2ef;border-radius:14px;background:#f7fafc;font-family:\"Outfit\",\"Roboto\",Arial,sans-serif}.ndts-meta{color:#2d799f;font-size:14px;font-weight:800;letter-spacing:.06em;text-transform:uppercase}.ndts-intro{margin:8px 0 14px;color:#405361;line-height:1.5}.ndts-progress{display:grid;grid-template-columns:repeat(7,minmax(0,1fr));gap:6px;margin:0;padding:0;list-style:none}.ndts-progress a{display:flex;align-items:center;justify-content:center;min-height:38px;padding:6px;border:1px solid #cbd9e2;border-radius:7px;background:#fff;color:#285c78!important;text-decoration:none!important;font-size:13px;font-weight:700;text-align:center}.ndts-progress a[aria-current=\"step\"]{border-color:#2d799f;background:#2d799f;color:#fff!important}.ndts-controls{display:flex;justify-content:space-between;align-items:center;gap:10px;margin-top:14px;flex-wrap:wrap}.ndts-controls a{color:#1261a0!important;font-weight:700;text-decoration:none!important}.ndts-bottom{max-width:1000px;margin:26px auto;padding:18px 20px;border-top:1px solid #d8e2ef;font-family:\"Outfit\",\"Roboto\",Arial,sans-serif}.ndts-finish{margin:0 0 18px;padding:22px;border:1px solid #d8e2ef;border-radius:12px;background:#f6f9fc}.ndts-btn{display:inline-block;margin:6px 8px 0 0;padding:11px 15px;border-radius:7px;background:#1261a0;color:#fff!important;text-decoration:none!important;font-weight:700}@media(max-width:760px){.ndts-progress{grid-template-columns:repeat(2,minmax(0,1fr))}}<\/style><nav class=\"ndts\" aria-label=\"Machine learning tutorial progress\"><div class=\"ndts-meta\">Machine learning tutorial \u00b7 Chapter 1 of 7<\/div><p class=\"ndts-intro\">This page is part of Chapter 1, <a href=\"https:\/\/www.neuraldesigner.com\/learning\/tutorials\/neural-networks-applications\/\">Model types<\/a>. Follow the sequence or use the progress links to open a specific topic. <a href=\"https:\/\/www.neuraldesigner.com\/learning\/machine-learning-tutorial\/\">Tutorial overview<\/a>.<\/p><ol class=\"ndts-progress\"><li><a href=\"https:\/\/www.neuraldesigner.com\/learning\/tutorials\/neural-networks-applications\/\" aria-current=\"step\" data-tutorial-nav=\"chapter-1\" onclick=\"if(typeof gtag==='function'){gtag('event','tutorial_nav_click',{tutorial_action:'progress',tutorial_chapter:'1',link_url:this.href});}\">1. Model types<\/a><\/li><li><a href=\"https:\/\/www.neuraldesigner.com\/learning\/tutorials\/data-set\/\" data-tutorial-nav=\"chapter-2\" onclick=\"if(typeof gtag==='function'){gtag('event','tutorial_nav_click',{tutorial_action:'progress',tutorial_chapter:'2',link_url:this.href});}\">2. Data set<\/a><\/li><li><a href=\"https:\/\/www.neuraldesigner.com\/learning\/tutorials\/neural-network\/\" data-tutorial-nav=\"chapter-3\" onclick=\"if(typeof gtag==='function'){gtag('event','tutorial_nav_click',{tutorial_action:'progress',tutorial_chapter:'3',link_url:this.href});}\">3. Neural network<\/a><\/li><li><a href=\"https:\/\/www.neuraldesigner.com\/learning\/tutorials\/training-strategy\/\" data-tutorial-nav=\"chapter-4\" onclick=\"if(typeof gtag==='function'){gtag('event','tutorial_nav_click',{tutorial_action:'progress',tutorial_chapter:'4',link_url:this.href});}\">4. Training strategy<\/a><\/li><li><a href=\"https:\/\/www.neuraldesigner.com\/learning\/tutorials\/model-selection\/\" data-tutorial-nav=\"chapter-5\" onclick=\"if(typeof gtag==='function'){gtag('event','tutorial_nav_click',{tutorial_action:'progress',tutorial_chapter:'5',link_url:this.href});}\">5. Model selection<\/a><\/li><li><a href=\"https:\/\/www.neuraldesigner.com\/learning\/tutorials\/testing-analysis\/\" data-tutorial-nav=\"chapter-6\" onclick=\"if(typeof gtag==='function'){gtag('event','tutorial_nav_click',{tutorial_action:'progress',tutorial_chapter:'6',link_url:this.href});}\">6. Testing analysis<\/a><\/li><li><a href=\"https:\/\/www.neuraldesigner.com\/learning\/tutorials\/model-deployment\/\" data-tutorial-nav=\"chapter-7\" onclick=\"if(typeof gtag==='function'){gtag('event','tutorial_nav_click',{tutorial_action:'progress',tutorial_chapter:'7',link_url:this.href});}\">7. Model deployment<\/a><\/li><\/ol><div class=\"ndts-controls\"><a href=\"https:\/\/www.neuraldesigner.com\/learning\/tutorials\/neural-networks-applications\/\" data-tutorial-nav=\"chapter\">\u2190 Model types<\/a><a href=\"https:\/\/www.neuraldesigner.com\/learning\/machine-learning-tutorial\/\">Overview<\/a><a href=\"https:\/\/www.neuraldesigner.com\/learning\/tutorials\/image-classification-model\/\" data-tutorial-nav=\"next\" onclick=\"if(typeof gtag==='function'){gtag('event','tutorial_nav_click',{tutorial_action:'next',tutorial_chapter:'1',link_url:this.href});}\">1.6. Image classification \u2192<\/a><\/div><\/nav><style>.ndg{width:100vw;margin-left:calc(50% - 50vw);background:#eeeeee;padding:22px 24px 12px;font-family:\"Outfit\",\"Roboto\",Arial,sans-serif;color:#1b2635}.ndg *{box-sizing:border-box}.ndg a{text-decoration:none}.ndg-wrap{width:min(100%,1000px);margin:0 auto}.ndg-lead{font-size:19px;line-height:1.6;color:#3a4a5a;font-weight:300;margin:0 0 22px}.ndg-lead a{color:#2d799f;font-weight:600}.ndg-herofig{margin:0 0 30px;text-align:center}.ndg-herofig img{max-width:min(540px,100%);height:auto}.ndg-eyebrow{margin:0 0 14px;text-align:center;color:#2d799f;font-size:13px;font-weight:800;letter-spacing:.14em;text-transform:uppercase}.ndg-toc{list-style:none;display:grid;grid-template-columns:repeat(3,minmax(0,1fr));gap:12px;margin:0 0 48px;padding:0}.ndg-toc a{display:flex;align-items:center;gap:10px;height:100%;padding:14px 16px;background:#f2f2f2;border-radius:12px;color:#12354b!important;font-size:15px;font-weight:600;line-height:1.25;box-shadow:-8px -8px 16px rgba(255,255,255,.9),8px 8px 16px rgba(30,83,116,.10)}.ndg-toc a:hover{color:#2d799f!important}.ndg-step{display:grid;grid-template-columns:72px 1fr;gap:26px;margin:0 0 34px;padding:34px 38px;background:#f2f2f2;border-radius:22px;box-shadow:-14px -14px 28px rgba(255,255,255,.92),14px 14px 28px rgba(30,83,116,.12);scroll-margin-top:90px}.ndg-ic{width:72px;height:72px;border-radius:50%;background:#e7f1f7;display:flex;align-items:center;justify-content:center;flex:0 0 72px}.ndg-ic img{width:38px!important;height:38px!important;object-fit:contain;margin:0!important;box-shadow:none!important;border-radius:0!important}.ndg-step__body{min-width:0}.ndg-step__body h2{display:flex!important;align-items:center!important;min-height:72px;margin:0 0 16px!important;padding:0!important;color:#001233;font-size:25px;font-weight:700;line-height:1.2}.ndg-step__body h3{margin:26px 0 12px;color:#12354b;font-size:19px;font-weight:600}.ndg-step__body p{margin:0 0 16px;font-size:17px;line-height:1.62;color:#33424f}.ndg-step__body a{color:#2d799f;font-weight:500}.ndg-step__body ul{margin:0 0 16px;padding-left:22px}.ndg-step__body li{margin:7px 0;font-size:16px;line-height:1.55;color:#33424f}.ndg-step__body img{display:block!important;width:auto!important;max-width:min(560px,100%)!important;height:auto!important;margin:22px auto!important;border-radius:12px!important;box-shadow:0 12px 28px rgba(0,18,51,.12)!important}.ndg-step__body figure{margin:22px auto!important;max-width:min(620px,100%)}.ndg-step__body figcaption{text-align:center;color:#6a7884;font-size:13px;margin-top:8px}.ndg-nav{display:flex;justify-content:space-between;gap:16px;margin:12px 0 8px;flex-wrap:wrap}.ndg-nav a{display:inline-flex;align-items:center;padding:13px 24px;border-radius:10px;background:#f2f2f2;color:#2d799f!important;font-weight:800;font-size:15px;box-shadow:-8px -8px 16px rgba(255,255,255,.92),8px 8px 16px rgba(30,83,116,.10)}.ndg-nav a:hover{color:#1f5f80!important}@media(max-width:820px){.ndg-toc{grid-template-columns:1fr}.ndg-step{grid-template-columns:1fr;gap:16px;padding:26px 22px}.ndg-ic{width:56px;height:56px;flex:0 0 56px}.ndg-step__body h2{min-height:0;font-size:22px}}@media(max-width:640px){.ndg{padding:12px 14px}}<\/style><div class=\"ndg\"><div class=\"ndg-wrap\"><div class=\"ndg-step\" id=\"TextClassification\"><div class=\"ndg-ic\"><img decoding=\"async\" src=\"https:\/\/www.neuraldesigner.com\/images\/text-classification-icon.svg\" alt=\"\" width=\"44\" height=\"44\" \/><\/div><div class=\"ndg-step__body\"><h2>1.5. Text classification<\/h2><p>Text classification is a natural language processing task in which text data is categorized into predefined labels or categories.<\/p>\n<p>The basic goal of a text classification problem is to model one or several target variables conditioned on the input text data.<\/p>\n<p>The objective here is to predict the category or label of a given text based on its content.<\/p>\n<p>In text classification applications, the targets are usually discrete variables such as categories, labels, or sentiments.<\/p>\n<p>Some examples are the following:<\/p>\n<ul>\n<li>Spam detection: Classifying emails as spam or not based on their content.<\/li>\n<li>Sentiment analysis: Classifying text data as positive, negative, or neutral based on the sentiment expressed.<\/li>\n<li>Topic classification: Classifying news articles into predefined topics such as politics, sports, technology, etc.<\/li>\n<li>Named entity recognition: Identifying and classifying named entities such as people, organizations, locations, etc.<\/li>\n<\/ul>\n<p>Text data are noisy in their own way. Typos, grammatical errors, abbreviations and passages unrelated to the label add variation that says nothing about the category, while the useful information lies in recurring words, phrases and patterns.<\/p>\n<p>The aim is a model that relies on those recurring patterns rather than on accidental details of the training documents, so that it also assigns the right category to texts it has never seen.<\/p>\n<\/div><\/div><p class=\"ndg-eyebrow\">All model types<\/p><ul class=\"ndg-toc\"><li><a href=\"https:\/\/www.neuraldesigner.com\/learning\/tutorials\/approximation-model\/\">1.1. Approximation (or function regression)<\/a><\/li><li><a href=\"https:\/\/www.neuraldesigner.com\/learning\/tutorials\/classification-model\/\">1.2. Classification (or pattern recognition)<\/a><\/li><li><a href=\"https:\/\/www.neuraldesigner.com\/learning\/tutorials\/forecasting-model\/\">1.3. Forecasting (or time series prediction)<\/a><\/li><li><a href=\"https:\/\/www.neuraldesigner.com\/learning\/tutorials\/anomaly-detection-model\/\">1.4. Anomaly detection<\/a><\/li><li><a href=\"https:\/\/www.neuraldesigner.com\/learning\/tutorials\/text-classification-model\/\" aria-current=\"page\">1.5. Text classification<\/a><\/li><li><a href=\"https:\/\/www.neuraldesigner.com\/learning\/tutorials\/image-classification-model\/\">1.6. Image classification model<\/a><\/li><\/ul><\/div><\/div><nav class=\"ndts-bottom\" aria-label=\"Tutorial chapter navigation\"><div class=\"ndts-controls\"><a href=\"https:\/\/www.neuraldesigner.com\/learning\/tutorials\/anomaly-detection-model\/\" data-tutorial-nav=\"previous\">\u2190 1.4. Anomaly detection<\/a><a href=\"https:\/\/www.neuraldesigner.com\/learning\/tutorials\/neural-networks-applications\/\">All model types<\/a><a href=\"https:\/\/www.neuraldesigner.com\/learning\/tutorials\/image-classification-model\/\" data-tutorial-nav=\"next\" onclick=\"if(typeof gtag==='function'){gtag('event','tutorial_nav_click',{tutorial_action:'next',tutorial_chapter:'1',link_url:this.href});}\">1.6. Image classification \u2192<\/a><\/div><\/nav>","protected":false},"author":122,"featured_media":2702,"template":"","categories":[30],"tags":[36],"class_list":["post-24379","learning","type-learning","status-publish","has-post-thumbnail","hentry","category-tutorials","tag-tutorials"],"acf":[],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v26.4 - https:\/\/yoast.com\/wordpress\/plugins\/seo\/ -->\n<title>Text Classification Models - Neural Designer<\/title>\n<meta name=\"description\" content=\"Learn how text classification models assign documents to predefined categories, with applications such as spam detection and sentiment analysis.\" \/>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/www.neuraldesigner.com\/learning\/tutorials\/text-classification-model\/\" \/>\n<meta property=\"og:locale\" content=\"en_US\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Text Classification Models - 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