{"id":24375,"date":"2026-10-17T16:19:37","date_gmt":"2026-10-17T14:19:37","guid":{"rendered":"https:\/\/www.neuraldesigner.com\/learning\/tutorials\/forecasting-model\/"},"modified":"2026-10-17T16:19:37","modified_gmt":"2026-10-17T14:19:37","slug":"forecasting-model","status":"publish","type":"learning","link":"https:\/\/www.neuraldesigner.com\/learning\/tutorials\/forecasting-model\/","title":{"rendered":"Model types: Forecasting (or time series prediction)"},"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\/anomaly-detection-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});}\">1.4. Anomaly detection \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=\"Forecasting\"><div class=\"ndg-ic\"><img decoding=\"async\" src=\"https:\/\/www.neuraldesigner.com\/images\/forecasting.svg\" alt=\"\" width=\"44\" height=\"44\" \/><\/div><div class=\"ndg-step__body\"><h2>1.3. Forecasting (or time series prediction)<\/h2><p>A forecasting model predicts the values that one or more variables will take in the future, using the values that they, and possibly other variables, took in the past.<\/p>\n<p>The data come as a time series: observations recorded at regular intervals, such as every hour, day or month. To train a neural network, the series is rearranged into samples. In Neural Designer, you choose the number of lags and the number of steps ahead: the inputs of each sample are the observations at the current time step and at the previous ones (the lags), and the targets are the values at the following time steps. After this rearrangement, a forecasting model is trained much like an approximation model.<\/p>\n<p>The following figure illustrates a forecast application: the model estimates the next value, <em>y<sub>t+1<\/sub><\/em>, from the current value, <em>y<sub>t<\/sub><\/em>, the previous one, <em>y<sub>t-1<\/sub><\/em>, and so on.<\/p>\n<p><img loading=\"lazy\" loading=\"lazy\" decoding=\"async\" style=\"max-width: 600px;\" src=\"https:\/\/www.neuraldesigner.com\/images\/forecasting.webp\" alt=\"Forecasting problem\" width=\"600\" height=\"350\" \/><\/p>\n<p>For instance, a car manufacturer can forecast next month&#8217;s sales of a model from its sales in previous months, its recent marketing actions and macroeconomic indicators.<\/p>\n<p>A forecasting model is only useful if its predictions hold beyond the period it was trained on. For that reason, it is good practice to test it on the most recent part of the series, which the model has not seen during training.<\/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\/\" aria-current=\"page\">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\/\">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\/classification-model\/\" data-tutorial-nav=\"previous\">\u2190 1.2. Classification<\/a><a href=\"https:\/\/www.neuraldesigner.com\/learning\/tutorials\/neural-networks-applications\/\">All model types<\/a><a href=\"https:\/\/www.neuraldesigner.com\/learning\/tutorials\/anomaly-detection-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});}\">1.4. Anomaly detection \u2192<\/a><\/div><\/nav>","protected":false},"author":122,"featured_media":2702,"template":"","categories":[30],"tags":[36],"class_list":["post-24375","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>Forecasting Models (Time Series Prediction) - Neural Designer<\/title>\n<meta name=\"description\" content=\"Learn how forecasting models predict future values of a time series from lags and steps ahead, and why they are tested on the most recent data.\" \/>\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\/forecasting-model\/\" \/>\n<meta property=\"og:locale\" content=\"en_US\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Forecasting Models (Time Series Prediction) - 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