{"id":6782,"date":"2024-03-14T06:58:00","date_gmt":"2024-03-14T06:58:00","guid":{"rendered":"https:\/\/www.pickl.ai\/blog\/?post_type=web-story&#038;p=6782"},"modified":"2024-03-15T07:05:40","modified_gmt":"2024-03-15T07:05:40","slug":"understanding-regression-in-machine-learning","status":"publish","type":"web-story","link":"https:\/\/www.pickl.ai\/blog\/web-stories\/understanding-regression-in-machine-learning\/","title":{"rendered":"Understanding Regression in Machine Learning"},"content":{"rendered":"<p><html amp=\"\" lang=\"en\"><head><meta charSet=\"utf-8\"\/><meta name=\"viewport\" content=\"width=device-width,minimum-scale=1,initial-scale=1\"\/><script async=\"\" src=\"https:\/\/cdn.ampproject.org\/v0.js\"><\/script><script async=\"\" src=\"https:\/\/cdn.ampproject.org\/v0\/amp-story-1.0.js\" custom-element=\"amp-story\"><\/script><link href=\"https:\/\/fonts.googleapis.com\/css2?display=swap&amp;family=Lora%3Awght%40700\" rel=\"stylesheet\"\/>\n<style 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name=\"web-stories-replace-head-start\"\/><title>Understanding Regression in Machine Learning<\/title><link rel=\"canonical\" href=\"https:\/\/pickl.ai\/blog\/?post_type=web-story&amp;p=6782\"\/><meta name=\"web-stories-replace-head-end\"\/><\/head><body><amp-story standalone=\"\" publisher=\"Pickl.AI\" publisher-logo-src=\"https:\/\/pickl.ai\/blog\/wp-content\/uploads\/2022\/01\/cropped-cropped-favicon.png\" title=\"Understanding Regression in Machine Learning\" poster-portrait-src=\"https:\/\/pickl.ai\/blog\/wp-content\/uploads\/2024\/03\/cropped-Machine-Learning.jpeg\"><amp-story-page id=\"87f96562-75a5-415f-8015-3088ba67b6f4\" auto-advance-after=\"7s\"><amp-story-grid-layer template=\"vertical\" aspect-ratio=\"412:618\" class=\"grid-layer\"><\/p>\n<div class=\"page-fullbleed-area\" style=\"background-color:#e0aaff\">\n<div class=\"page-safe-area\">\n<div style=\"position:absolute;pointer-events:none;left:0;top:-9.25926%;width:100%;height:118.51852%;opacity:1\">\n<div style=\"pointer-events:initial;width:100%;height:100%;display:block;position:absolute;top:0;left:0;z-index:0\" class=\"mask\" id=\"el-a4d84387-39d5-4ec6-ac72-715cf1ba1fab\">\n<div class=\"fill\" style=\"will-change:transform\"><\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<p><\/amp-story-grid-layer><amp-story-grid-layer template=\"vertical\" aspect-ratio=\"412:618\" class=\"grid-layer\"><\/p>\n<div class=\"page-fullbleed-area\">\n<div class=\"page-safe-area\">\n<div style=\"position:absolute;pointer-events:none;left:11.65049%;top:37.86408%;width:76.45631%;height:18.93204%;opacity:1\">\n<div style=\"pointer-events:initial;width:100%;height:100%;display:block;position:absolute;top:0;left:0;z-index:0;border-radius:0.6349206349206349% 0.6349206349206349% 0.6349206349206349% 0.6349206349206349% \/ 1.7094017094017095% 1.7094017094017095% 1.7094017094017095% 1.7094017094017095%\" id=\"el-f04ffa6a-a95c-4714-85ee-7133f2b8a6fd\">\n<h2 id=\"understanding-regression-in-machine-learning\" class=\"fill text-wrapper\" style=\"white-space:pre-line;overflow-wrap:break-word;word-break:break-word;margin:0.4571428571428575% 0;font-family:&quot;Lora&quot;,serif;font-size:0.517799em;line-height:1.19;text-align:center;padding:0;color:#000000\"><span><span style=\"font-weight: 700; color: #ffffb7\">Understanding Regression in Machine Learning<\/span><\/span><\/h2>\n<\/div>\n<\/div>\n<div style=\"position:absolute;pointer-events:none;left:11.65049%;top:60.67961%;width:76.45631%;height:27.50809%;opacity:1\">\n<div style=\"pointer-events:initial;width:100%;height:100%;display:block;position:absolute;top:0;left:0;z-index:0;border-radius:0.6349206349206349% 0.6349206349206349% 0.6349206349206349% 0.6349206349206349% \/ 1.1764705882352942% 1.1764705882352942% 1.1764705882352942% 1.1764705882352942%\" id=\"el-bcf93fa4-bf45-4003-abcd-d10197e9921f\">\n<p class=\"fill text-wrapper\" style=\"white-space:pre-line;overflow-wrap:break-word;word-break:break-word;margin:0.2539682539682542% 0;font-family:&quot;Lora&quot;,serif;font-size:0.323625em;line-height:1.2;text-align:center;padding:0;color:#000000\"><span><span style=\"font-weight: 700; color: #590d22\">Regression is a type of supervised Machine Learning algorithm that is used to recreate the relationship between one or more independent variables and dependent variables.<\/span><\/span><\/p>\n<\/div>\n<\/div>\n<div style=\"position:absolute;pointer-events:none;left:11.65049%;top:0;width:76.45631%;height:33.98058%;opacity:1\">\n<div style=\"pointer-events:initial;width:100%;height:100%;display:block;position:absolute;top:0;left:0;z-index:0\" class=\"mask\" id=\"el-07292bb8-e1f5-4cf4-a78a-f8e3785b8b27\">\n<div style=\"position:absolute;width:108.71211%;height:100%;left:-4.35606%;top:0%\" data-leaf-element=\"true\"><amp-img layout=\"fill\" src=\"https:\/\/pickl.ai\/blog\/wp-content\/uploads\/2024\/03\/Machine-Learning.jpeg\" alt=\"Machine Learning\" srcSet=\"https:\/\/pickl.ai\/blog\/wp-content\/uploads\/2024\/03\/Machine-Learning.jpeg 287w,https:\/\/pickl.ai\/blog\/wp-content\/uploads\/2024\/03\/Machine-Learning-150x92.jpeg 150w\" sizes=\"(min-width: 1024px) 34vh, 76vw\" disable-inline-width=\"true\"><\/amp-img><\/div>\n<\/div>\n<\/div>\n<div style=\"position:absolute;pointer-events:none;left:11.16505%;top:95.14563%;width:75.48544%;height:6.31068%;opacity:1\">\n<div style=\"pointer-events:initial;width:100%;height:100%;display:block;position:absolute;top:0;left:0;z-index:0;border-radius:0.6430868167202572% 0.6430868167202572% 0.6430868167202572% 0.6430868167202572% \/ 5.128205128205128% 5.128205128205128% 5.128205128205128% 5.128205128205128%\" id=\"el-1aada695-a869-4494-b0b1-2994f223d878\"><a href=\"https:\/\/pickl.ai\/blog\/regression-in-machine-learning-types-examples\/\" target=\"_blank\" rel=\"noreferrer noopener\" style=\"width:100%;height:100%;display:block;position:absolute;top:0;left:0\"><\/p>\n<h2 id=\"learn-more\" class=\"fill text-wrapper\" style=\"white-space:pre-line;overflow-wrap:break-word;word-break:break-word;margin:0.3858520900321541% 0;font-family:&quot;Lora&quot;,serif;font-size:0.485437em;line-height:1.2;text-align:center;padding:0;color:#000000\"><span><span style=\"font-weight: 700\">Learn More<\/span><\/span><\/h2>\n<p><\/a><\/div>\n<\/div>\n<\/div>\n<\/div>\n<p><\/amp-story-grid-layer><\/amp-story-page><amp-story-page id=\"9dcbca80-311c-4fe7-970f-2a84f14f44ef\" auto-advance-after=\"7s\"><amp-story-grid-layer template=\"vertical\" aspect-ratio=\"412:618\" class=\"grid-layer\"><\/p>\n<div class=\"page-fullbleed-area\" style=\"background-color:#ffffb7\">\n<div class=\"page-safe-area\">\n<div style=\"position:absolute;pointer-events:none;left:0;top:-9.25926%;width:100%;height:118.51852%;opacity:1\">\n<div style=\"pointer-events:initial;width:100%;height:100%;display:block;position:absolute;top:0;left:0;z-index:0\" class=\"mask\" id=\"el-8720e6e2-4f4b-4bf3-94aa-17b500d89558\">\n<div class=\"fill\" style=\"will-change:transform\"><\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<p><\/amp-story-grid-layer><amp-story-grid-layer template=\"vertical\" aspect-ratio=\"412:618\" class=\"grid-layer\"><\/p>\n<div class=\"page-fullbleed-area\">\n<div class=\"page-safe-area\">\n<div style=\"position:absolute;pointer-events:none;left:11.8932%;top:42.88026%;width:76.45631%;height:14.40129%;opacity:1\">\n<div style=\"pointer-events:initial;width:100%;height:100%;display:block;position:absolute;top:0;left:0;z-index:0;border-radius:0.6349206349206349% 0.6349206349206349% 0.6349206349206349% 0.6349206349206349% \/ 2.247191011235955% 2.247191011235955% 2.247191011235955% 2.247191011235955%\" id=\"el-3f90ec98-e4d2-4449-a670-09661d06d8b0\">\n<h1 id=\"purpose-and-analysis\" class=\"fill text-wrapper\" style=\"white-space:pre-line;overflow-wrap:break-word;word-break:break-word;margin:0.5142857142857146% 0;font-family:&quot;Lora&quot;,serif;font-size:0.582524em;line-height:1.19;text-align:center;padding:0;color:#000000\"><span><span style=\"font-weight: 700; color: #e06e04\">Purpose and Analysis<\/span><\/span><\/h1>\n<\/div>\n<\/div>\n<div style=\"position:absolute;pointer-events:none;left:11.65049%;top:60.19417%;width:76.45631%;height:27.50809%;opacity:1\">\n<div style=\"pointer-events:initial;width:100%;height:100%;display:block;position:absolute;top:0;left:0;z-index:0;border-radius:0.6349206349206349% 0.6349206349206349% 0.6349206349206349% 0.6349206349206349% \/ 1.1764705882352942% 1.1764705882352942% 1.1764705882352942% 1.1764705882352942%\" id=\"el-9137978a-072a-4c16-a352-059e0f9f54f6\">\n<p class=\"fill text-wrapper\" style=\"white-space:pre-line;overflow-wrap:break-word;word-break:break-word;margin:0.2539682539682542% 0;font-family:&quot;Lora&quot;,serif;font-size:0.323625em;line-height:1.2;text-align:center;padding:0;color:#000000\"><span><span style=\"font-weight: 700; color: #003bad\">Regression analysis helps us understand how the value of the target variable varies with respect to one independent variable while other independent variables remain constant.<\/span><\/span><\/p>\n<\/div>\n<\/div>\n<div style=\"position:absolute;pointer-events:none;left:11.8932%;top:93.52751%;width:75.97087%;height:6.14887%;opacity:1\">\n<div style=\"pointer-events:initial;width:100%;height:100%;display:block;position:absolute;top:0;left:0;z-index:0;border-radius:0.6389776357827476% 0.6389776357827476% 0.6389776357827476% 0.6389776357827476% \/ 5.263157894736842% 5.263157894736842% 5.263157894736842% 5.263157894736842%\" id=\"el-51fcc55a-3461-4da5-8d04-0e1afaabfec2\"><a href=\"https:\/\/pickl.ai\/blog\/career-options-after-bca-pickl-ai\/\" target=\"_blank\" rel=\"noreferrer noopener\" style=\"width:100%;height:100%;display:block;position:absolute;top:0;left:0\"><\/p>\n<h2 id=\"learn-more-2\" class=\"fill text-wrapper\" style=\"white-space:pre-line;overflow-wrap:break-word;word-break:break-word;margin:0.3833865814696484% 0;font-family:&quot;Lora&quot;,serif;font-size:0.485437em;line-height:1.2;text-align:center;padding:0;color:#000000\"><span><span style=\"font-weight: 700; color: #e06e04\">Learn More<\/span><\/span><\/h2>\n<p><\/a><\/div>\n<\/div>\n<div style=\"position:absolute;pointer-events:none;left:11.65049%;top:0;width:75.97087%;height:39.96764%;opacity:1\">\n<div style=\"pointer-events:initial;width:100%;height:100%;display:block;position:absolute;top:0;left:0;z-index:0\" class=\"mask\" id=\"el-0602010c-8276-46a3-91a1-565d93c8f880\">\n<div style=\"position:absolute;width:100%;height:125.78196%;left:0%;top:-12.89098%\" data-leaf-element=\"true\"><amp-img layout=\"fill\" src=\"https:\/\/pickl.ai\/blog\/wp-content\/uploads\/2024\/03\/machine-learning-pillar-page-overview.jpeg\" alt=\"machine-learning-pillar-page-overview\" srcSet=\"https:\/\/pickl.ai\/blog\/wp-content\/uploads\/2024\/03\/machine-learning-pillar-page-overview.jpeg 810w,https:\/\/pickl.ai\/blog\/wp-content\/uploads\/2024\/03\/machine-learning-pillar-page-overview-768x762.jpeg 768w,https:\/\/pickl.ai\/blog\/wp-content\/uploads\/2024\/03\/machine-learning-pillar-page-overview-300x298.jpeg 300w,https:\/\/pickl.ai\/blog\/wp-content\/uploads\/2024\/03\/machine-learning-pillar-page-overview-150x150.jpeg 150w,https:\/\/pickl.ai\/blog\/wp-content\/uploads\/2024\/03\/machine-learning-pillar-page-overview-96x96.jpeg 96w\" sizes=\"(min-width: 1024px) 34vh, 76vw\" disable-inline-width=\"true\"><\/amp-img><\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<p><\/amp-story-grid-layer><\/amp-story-page><amp-story-page id=\"f37739dc-67d3-49ae-9030-531d941346dc\" auto-advance-after=\"7s\"><amp-story-grid-layer template=\"vertical\" aspect-ratio=\"412:618\" class=\"grid-layer\"><\/p>\n<div class=\"page-fullbleed-area\" style=\"background-color:#e03568\">\n<div class=\"page-safe-area\">\n<div style=\"position:absolute;pointer-events:none;left:0;top:-9.25926%;width:100%;height:118.51852%;opacity:1\">\n<div style=\"pointer-events:initial;width:100%;height:100%;display:block;position:absolute;top:0;left:0;z-index:0\" class=\"mask\" id=\"el-b1734fcf-a988-44a9-b077-6cd0772e1a68\">\n<div class=\"fill\" style=\"will-change:transform\"><\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<p><\/amp-story-grid-layer><amp-story-grid-layer template=\"vertical\" aspect-ratio=\"412:618\" class=\"grid-layer\"><\/p>\n<div class=\"page-fullbleed-area\">\n<div class=\"page-safe-area\">\n<div style=\"position:absolute;pointer-events:none;left:11.65049%;top:42.39482%;width:76.45631%;height:14.40129%;opacity:1\">\n<div style=\"pointer-events:initial;width:100%;height:100%;display:block;position:absolute;top:0;left:0;z-index:0;border-radius:0.6349206349206349% 0.6349206349206349% 0.6349206349206349% 0.6349206349206349% \/ 2.247191011235955% 2.247191011235955% 2.247191011235955% 2.247191011235955%\" id=\"el-933e4b1d-9256-49eb-8353-f909ba52793c\">\n<h1 id=\"major-types-of-regression\" class=\"fill text-wrapper\" style=\"white-space:pre-line;overflow-wrap:break-word;word-break:break-word;margin:0.5142857142857146% 0;font-family:&quot;Lora&quot;,serif;font-size:0.582524em;line-height:1.19;text-align:center;padding:0;color:#000000\"><span><span style=\"font-weight: 700; color: #ffffb7\">Major Types of Regression<\/span><\/span><\/h1>\n<\/div>\n<\/div>\n<div style=\"position:absolute;pointer-events:none;left:11.65049%;top:60.84142%;width:76.45631%;height:39.15858%;opacity:1\">\n<div style=\"pointer-events:initial;width:100%;height:100%;display:block;position:absolute;top:0;left:0;z-index:0;border-radius:0.6349206349206349% 0.6349206349206349% 0.6349206349206349% 0.6349206349206349% \/ 0.8264462809917356% 0.8264462809917356% 0.8264462809917356% 0.8264462809917356%\" id=\"el-c26f42c6-f885-4d69-9cfc-bf96b10fbfe0\">\n<p class=\"fill text-wrapper\" style=\"white-space:pre-line;overflow-wrap:break-word;word-break:break-word;margin:0.2539682539682542% 0;font-family:&quot;Lora&quot;,serif;font-size:0.323625em;line-height:1.2;text-align:center;padding:0;color:#000000\"><span><span style=\"font-weight: 700; color: #003bad\">Linear Regression<\/span><br \/>\n<span style=\"font-weight: 700; color: #003bad\">Multiple Linear Regression<\/span><br \/>\n<span style=\"font-weight: 700; color: #003bad\">Polynomial Regression<\/span><br \/>\n<span style=\"font-weight: 700; color: #003bad\">Ridge Regression (L2 Regularization)<\/span><br \/>\n<span style=\"font-weight: 700; color: #003bad\">Lasso Regression (L1 Regularization)<\/span><br \/>\n<span style=\"font-weight: 700; color: #003bad\">Decision Tree Regression<\/span><br \/>\n<span style=\"font-weight: 700; color: #003bad\">Logistic Regression<\/span><br \/>\n<span style=\"font-weight: 700; color: #003bad\">Poisson Regression<\/span><\/span><\/p>\n<\/div>\n<\/div>\n<div style=\"position:absolute;pointer-events:none;left:11.65049%;top:0;width:80.09709%;height:38.51133%;opacity:1\">\n<div style=\"pointer-events:initial;width:100%;height:100%;display:block;position:absolute;top:0;left:0;z-index:0\" class=\"mask\" id=\"el-c7b8b9f0-50ec-45db-892f-eb9ed9bb65f4\">\n<div style=\"position:absolute;width:100%;height:100.24618%;left:0%;top:-0.12309%\" data-leaf-element=\"true\"><amp-img layout=\"fill\" src=\"\" alt=\"1_0V_GsMAi2zN0OcNi7hm-vw\"><\/amp-img><\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<p><\/amp-story-grid-layer><\/amp-story-page><amp-story-page id=\"46efaf60-e875-4218-98f6-9c02f865ec87\" auto-advance-after=\"7s\"><amp-story-grid-layer template=\"vertical\" aspect-ratio=\"412:618\" class=\"grid-layer\"><\/p>\n<div class=\"page-fullbleed-area\" style=\"background-color:#bc8a5f\">\n<div class=\"page-safe-area\">\n<div style=\"position:absolute;pointer-events:none;left:0;top:-9.25926%;width:100%;height:118.51852%;opacity:1\">\n<div style=\"pointer-events:initial;width:100%;height:100%;display:block;position:absolute;top:0;left:0;z-index:0\" class=\"mask\" id=\"el-da6ee4e3-1ea8-4922-a960-df7c54a709b0\">\n<div class=\"fill\" style=\"will-change:transform\"><\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<p><\/amp-story-grid-layer><amp-story-grid-layer template=\"vertical\" aspect-ratio=\"412:618\" class=\"grid-layer\"><\/p>\n<div class=\"page-fullbleed-area\">\n<div class=\"page-safe-area\">\n<div style=\"position:absolute;pointer-events:none;left:11.65049%;top:47.73463%;width:73.54369%;height:14.40129%;opacity:1\">\n<div style=\"pointer-events:initial;width:100%;height:100%;display:block;position:absolute;top:0;left:0;z-index:0;border-radius:0.6600660066006601% 0.6600660066006601% 0.6600660066006601% 0.6600660066006601% \/ 2.247191011235955% 2.247191011235955% 2.247191011235955% 2.247191011235955%\" id=\"el-f211bd08-c5d4-4c81-88ac-89599d48c4f0\">\n<h1 id=\"other-types-of-regression\" class=\"fill text-wrapper\" style=\"white-space:pre-line;overflow-wrap:break-word;word-break:break-word;margin:0.5346534653465349% 0;font-family:&quot;Lora&quot;,serif;font-size:0.582524em;line-height:1.19;text-align:center;padding:0;color:#000000\"><span><span style=\"font-weight: 700; color: #4b1283\">Other Types of Regression<\/span><\/span><\/h1>\n<\/div>\n<\/div>\n<div style=\"position:absolute;pointer-events:none;left:11.65049%;top:64.07767%;width:76.45631%;height:31.71521%;opacity:1\">\n<div style=\"pointer-events:initial;width:100%;height:100%;display:block;position:absolute;top:0;left:0;z-index:0;border-radius:0.6349206349206349% 0.6349206349206349% 0.6349206349206349% 0.6349206349206349% \/ 1.0204081632653061% 1.0204081632653061% 1.0204081632653061% 1.0204081632653061%\" id=\"el-df90d544-57ca-49c6-96fa-d133f0d5152b\">\n<p class=\"fill text-wrapper\" style=\"white-space:pre-line;overflow-wrap:break-word;word-break:break-word;margin:0.22857142857142876% 0;font-family:&quot;Lora&quot;,serif;font-size:0.291262em;line-height:1.2;text-align:center;padding:0;color:#000000\"><span><span style=\"font-weight: 700; color: #d4e4c0\">Negative Binomial Regression<\/span><br \/>\n<span style=\"font-weight: 700; color: #d4e4c0\">Cox Regression (Proportional Hazards Model<\/span><br \/>\n<span style=\"font-weight: 700; color: #d4e4c0\">Stepwise Regression<\/span><br \/>\n<span style=\"font-weight: 700; color: #d4e4c0\">Time Series Regression<\/span><br \/>\n<span style=\"font-weight: 700; color: #d4e4c0\">Panel Data Regression (Fixed Effects and Random Effects Models)<\/span><br \/>\n<span style=\"font-weight: 700; color: #d4e4c0\">Bayesian Regression<\/span><br \/>\n<span style=\"font-weight: 700; color: #d4e4c0\">Quantile Regression<\/span><\/span><\/p>\n<\/div>\n<\/div>\n<div style=\"position:absolute;pointer-events:none;left:11.65049%;top:96.92557%;width:76.45631%;height:6.31068%;opacity:1\">\n<div style=\"pointer-events:initial;width:100%;height:100%;display:block;position:absolute;top:0;left:0;z-index:0;border-radius:0.6349206349206349% 0.6349206349206349% 0.6349206349206349% 0.6349206349206349% \/ 5.128205128205128% 5.128205128205128% 5.128205128205128% 5.128205128205128%\" id=\"el-ae551062-0bf9-423e-9721-829a1c091b46\"><a href=\"https:\/\/pickl.ai\/blog\/what-is-data-observability-tools-and-applications\/\" data-tooltip-icon=\"https:\/\/pickl.ai\/blog\/wp-content\/uploads\/2023\/10\/what-is-data-observability.jpg\" data-tooltip-text=\"Data Observability Tools and Its Key Applications\" target=\"_blank\" rel=\"noreferrer noopener\" style=\"width:100%;height:100%;display:block;position:absolute;top:0;left:0\"><\/p>\n<h2 id=\"learn-more-3\" class=\"fill text-wrapper\" style=\"white-space:pre-line;overflow-wrap:break-word;word-break:break-word;margin:0.3809523809523807% 0;font-family:&quot;Lora&quot;,serif;font-size:0.485437em;line-height:1.2;text-align:center;padding:0;color:#000000\"><span><span style=\"font-weight: 700; color: #4b1283\">Learn More<\/span><\/span><\/h2>\n<p><\/a><\/div>\n<\/div>\n<div style=\"position:absolute;pointer-events:none;left:11.65049%;top:0;width:76.45631%;height:45.79288%;opacity:1\">\n<div style=\"pointer-events:initial;width:100%;height:100%;display:block;position:absolute;top:0;left:0;z-index:0\" class=\"mask\" id=\"el-33eec548-bb9e-4585-b05e-02bf2c2427ca\">\n<div style=\"position:absolute;width:100%;height:103.81453%;left:0%;top:-1.90727%\" data-leaf-element=\"true\"><amp-img layout=\"fill\" src=\"https:\/\/pickl.ai\/blog\/wp-content\/uploads\/2024\/03\/Types-of-Regression-1.png\" alt=\"Types-of-Regression-1\" srcSet=\"https:\/\/pickl.ai\/blog\/wp-content\/uploads\/2024\/03\/Types-of-Regression-1.png 1025w,https:\/\/pickl.ai\/blog\/wp-content\/uploads\/2024\/03\/Types-of-Regression-1-768x716.png 768w,https:\/\/pickl.ai\/blog\/wp-content\/uploads\/2024\/03\/Types-of-Regression-1-300x280.png 300w,https:\/\/pickl.ai\/blog\/wp-content\/uploads\/2024\/03\/Types-of-Regression-1-150x140.png 150w\" sizes=\"(min-width: 1024px) 34vh, 76vw\" disable-inline-width=\"true\"><\/amp-img><\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<p><\/amp-story-grid-layer><\/amp-story-page><amp-story-page id=\"969d6255-a4f3-40f7-acde-d233487f9b86\" auto-advance-after=\"7s\"><amp-story-grid-layer template=\"vertical\" aspect-ratio=\"412:618\" class=\"grid-layer\"><\/p>\n<div class=\"page-fullbleed-area\" style=\"background-color:#6d9fff\">\n<div class=\"page-safe-area\">\n<div style=\"position:absolute;pointer-events:none;left:0;top:-9.25926%;width:100%;height:118.51852%;opacity:1\">\n<div style=\"pointer-events:initial;width:100%;height:100%;display:block;position:absolute;top:0;left:0;z-index:0\" class=\"mask\" id=\"el-22d13067-7380-42b0-be9a-26f08f96fd4f\">\n<div class=\"fill\" style=\"will-change:transform\"><\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<p><\/amp-story-grid-layer><amp-story-grid-layer template=\"vertical\" aspect-ratio=\"412:618\" class=\"grid-layer\"><\/p>\n<div class=\"page-fullbleed-area\">\n<div class=\"page-safe-area\">\n<div style=\"position:absolute;pointer-events:none;left:11.40777%;top:45.95469%;width:76.45631%;height:7.44337%;opacity:1\">\n<div style=\"pointer-events:initial;width:100%;height:100%;display:block;position:absolute;top:0;left:0;z-index:0;border-radius:0.6349206349206349% 0.6349206349206349% 0.6349206349206349% 0.6349206349206349% \/ 4.3478260869565215% 4.3478260869565215% 4.3478260869565215% 4.3478260869565215%\" id=\"el-cc89120d-663a-462f-9c73-2aa95566c648\">\n<h1 id=\"functionality\" class=\"fill text-wrapper\" style=\"white-space:pre-line;overflow-wrap:break-word;word-break:break-word;margin:0.5142857142857146% 0;font-family:&quot;Lora&quot;,serif;font-size:0.582524em;line-height:1.19;text-align:center;padding:0;color:#000000\"><span><span style=\"font-weight: 700\">Functionality<\/span><\/span><\/h1>\n<\/div>\n<\/div>\n<div style=\"position:absolute;pointer-events:none;left:11.8932%;top:58.25243%;width:76.45631%;height:30.09709%;opacity:1\">\n<div style=\"pointer-events:initial;width:100%;height:100%;display:block;position:absolute;top:0;left:0;z-index:0;border-radius:0.6349206349206349% 0.6349206349206349% 0.6349206349206349% 0.6349206349206349% \/ 1.0752688172043012% 1.0752688172043012% 1.0752688172043012% 1.0752688172043012%\" id=\"el-ed5ad293-f0e5-4244-a672-a5f171d720e7\">\n<h3 id=\"regression-analysis-efficiently-finds-the-line-that-best-fits-all-data-points-this-line-maximises-the-models-accuracy-by-minimising-the-distance-from-each-data-point\" class=\"fill text-wrapper\" style=\"white-space:pre-line;overflow-wrap:break-word;word-break:break-word;margin:0.2793650793650796% 0;font-family:&quot;Lora&quot;,serif;font-size:0.355987em;line-height:1.2;text-align:left;padding:0;color:#000000\"><span><span style=\"font-weight: 700; color: #590d22\">Regression analysis efficiently finds the line that best fits all data points. This line maximises the model&#8217;s accuracy by minimising the distance from each data point.<\/span><\/span><\/h3>\n<\/div>\n<\/div>\n<div style=\"position:absolute;pointer-events:none;left:11.65049%;top:93.20388%;width:76.45631%;height:6.14887%;opacity:1\">\n<div style=\"pointer-events:initial;width:100%;height:100%;display:block;position:absolute;top:0;left:0;z-index:0;border-radius:0.6349206349206349% 0.6349206349206349% 0.6349206349206349% 0.6349206349206349% \/ 5.263157894736842% 5.263157894736842% 5.263157894736842% 5.263157894736842%\" id=\"el-fc8abaec-9046-4be0-a436-14672de50de0\"><a href=\"https:\/\/pickl.ai\/blog\/scikit-learn-cheat-sheet\/\" data-tooltip-icon=\"https:\/\/pickl.ai\/blog\/wp-content\/uploads\/2023\/11\/Scikit-Learn-Cheat-Sheet.jpg\" data-tooltip-text=\"Scikit-Learn Cheat Sheet: A Comprehensive Guide\" target=\"_blank\" rel=\"noreferrer noopener\" style=\"width:100%;height:100%;display:block;position:absolute;top:0;left:0\"><\/p>\n<h2 id=\"learn-more-4\" class=\"fill text-wrapper\" style=\"white-space:pre-line;overflow-wrap:break-word;word-break:break-word;margin:0.3809523809523807% 0;font-family:&quot;Lora&quot;,serif;font-size:0.485437em;line-height:1.2;text-align:center;padding:0;color:#000000\"><span><span style=\"font-weight: 700\">Learn More<\/span><\/span><\/h2>\n<p><\/a><\/div>\n<\/div>\n<div style=\"position:absolute;pointer-events:none;left:11.40777%;top:0;width:76.45631%;height:42.39482%;opacity:1\">\n<div style=\"pointer-events:initial;width:100%;height:100%;display:block;position:absolute;top:0;left:0;z-index:0\" class=\"mask\" id=\"el-1f684ca4-1a1c-4f92-b2ab-81cdebec7df4\">\n<div style=\"position:absolute;width:100%;height:110.55114%;left:0%;top:-5.27557%\" data-leaf-element=\"true\"><amp-img layout=\"fill\" src=\"https:\/\/pickl.ai\/blog\/wp-content\/uploads\/2024\/03\/Machine-Learning-its-Characteristics.png\" alt=\"Machine-Learning-its-Characteristics\" srcSet=\"https:\/\/pickl.ai\/blog\/wp-content\/uploads\/2024\/03\/Machine-Learning-its-Characteristics.png 646w,https:\/\/pickl.ai\/blog\/wp-content\/uploads\/2024\/03\/Machine-Learning-its-Characteristics-300x276.png 300w,https:\/\/pickl.ai\/blog\/wp-content\/uploads\/2024\/03\/Machine-Learning-its-Characteristics-150x138.png 150w\" sizes=\"(min-width: 1024px) 34vh, 76vw\" disable-inline-width=\"true\"><\/amp-img><\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<p><\/amp-story-grid-layer><\/amp-story-page><amp-story-page id=\"973e7d1a-70ad-455b-bb77-a9143ae41d2a\" auto-advance-after=\"7s\"><amp-story-grid-layer template=\"vertical\" aspect-ratio=\"412:618\" class=\"grid-layer\"><\/p>\n<div class=\"page-fullbleed-area\" style=\"background-color:#891bcf\">\n<div class=\"page-safe-area\">\n<div style=\"position:absolute;pointer-events:none;left:0;top:-9.25926%;width:100%;height:118.51852%;opacity:1\">\n<div style=\"pointer-events:initial;width:100%;height:100%;display:block;position:absolute;top:0;left:0;z-index:0\" class=\"mask\" id=\"el-4cf77503-4d10-422d-a1f3-752838ee5e62\">\n<div class=\"fill\" style=\"will-change:transform\"><\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<p><\/amp-story-grid-layer><amp-story-grid-layer template=\"vertical\" aspect-ratio=\"412:618\" class=\"grid-layer\"><\/p>\n<div class=\"page-fullbleed-area\">\n<div class=\"page-safe-area\">\n<div style=\"position:absolute;pointer-events:none;left:23.30097%;top:39.32039%;width:76.45631%;height:7.76699%;opacity:1\">\n<div style=\"pointer-events:initial;width:100%;height:100%;display:block;position:absolute;top:0;left:0;z-index:0;border-radius:0.6349206349206349% 0.6349206349206349% 0.6349206349206349% 0.6349206349206349% \/ 4.166666666666666% 4.166666666666666% 4.166666666666666% 4.166666666666666%\" id=\"el-c4599fb7-04ab-4f57-9495-2133d755dd4c\">\n<h1 id=\"conclusion\" class=\"fill text-wrapper\" style=\"white-space:pre-line;overflow-wrap:break-word;word-break:break-word;margin:0.5142857142857146% 0;font-family:&quot;Lora&quot;,serif;font-size:0.582524em;line-height:1.19;text-align:left;padding:0;color:#000000\"><span><span style=\"font-weight: 700\">Conclusion<\/span><\/span><\/h1>\n<\/div>\n<\/div>\n<div style=\"position:absolute;pointer-events:none;left:14.32039%;top:52.75081%;width:74.02913%;height:38.83495%;opacity:1\">\n<div style=\"pointer-events:initial;width:100%;height:100%;display:block;position:absolute;top:0;left:0;z-index:0;border-radius:0.6557377049180327% 0.6557377049180327% 0.6557377049180327% 0.6557377049180327% \/ 0.8333333333333334% 0.8333333333333334% 0.8333333333333334% 0.8333333333333334%\" id=\"el-6e4ca58d-f677-447a-a1b1-ef86b28a9e7a\">\n<h3 id=\"regression-is-a-supervised-machine-learning-technique-that-assists-in-determining-the-correlation-between-variables-using-regression-you-can-predict-the-continuous-output-variable-using-one-or-more\" class=\"fill text-wrapper\" style=\"white-space:pre-line;overflow-wrap:break-word;word-break:break-word;margin:0.28852459016393467% 0;font-family:&quot;Lora&quot;,serif;font-size:0.355987em;line-height:1.2;text-align:left;padding:0;color:#000000\"><span><span style=\"font-weight: 700; color: #fff\">Regression is a supervised machine-learning technique that assists in determining the correlation between variables. Using regression, you can predict the continuous output variable using one or more predictor variables.<\/span><\/span><\/h3>\n<\/div>\n<\/div>\n<div style=\"position:absolute;pointer-events:none;left:14.32039%;top:97.24919%;width:74.02913%;height:5.66343%;opacity:1\">\n<div style=\"pointer-events:initial;width:100%;height:100%;display:block;position:absolute;top:0;left:0;z-index:0;border-radius:0.6557377049180327% 0.6557377049180327% 0.6557377049180327% 0.6557377049180327% \/ 5.714285714285714% 5.714285714285714% 5.714285714285714% 5.714285714285714%\" id=\"el-855f3c5b-ab10-4c49-91d3-5a1427bd6f3e\"><a href=\"https:\/\/pickl.ai\/blog\/what-is-scratch-programming-working-and-applications\/\" target=\"_blank\" rel=\"noreferrer noopener\" style=\"width:100%;height:100%;display:block;position:absolute;top:0;left:0\"><\/p>\n<h2 id=\"learn-more-5\" class=\"fill text-wrapper\" style=\"white-space:pre-line;overflow-wrap:break-word;word-break:break-word;margin:0.3540983606557383% 0;font-family:&quot;Lora&quot;,serif;font-size:0.436893em;line-height:1.2;text-align:center;padding:0;color:#000000\"><span><span style=\"font-weight: 700\">Learn More<\/span><\/span><\/h2>\n<p><\/a><\/div>\n<\/div>\n<div style=\"position:absolute;pointer-events:none;left:11.65049%;top:0;width:76.45631%;height:33.00971%;opacity:1\">\n<div style=\"pointer-events:initial;width:100%;height:100%;display:block;position:absolute;top:0;left:0;z-index:0\" class=\"mask\" id=\"el-82c7693b-49d7-4b8f-885b-e56182ce169c\">\n<div style=\"position:absolute;width:100%;height:102.75401%;left:0%;top:-1.377%\" data-leaf-element=\"true\"><amp-img layout=\"fill\" src=\"https:\/\/pickl.ai\/blog\/wp-content\/uploads\/2024\/03\/download-13.jpeg\" alt=\"download (13)\" srcSet=\"https:\/\/pickl.ai\/blog\/wp-content\/uploads\/2024\/03\/download-13.jpeg 275w,https:\/\/pickl.ai\/blog\/wp-content\/uploads\/2024\/03\/download-13-150x100.jpeg 150w\" sizes=\"(min-width: 1024px) 34vh, 76vw\" disable-inline-width=\"true\"><\/amp-img><\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<p><\/amp-story-grid-layer><\/amp-story-page><\/amp-story><\/body><\/html><\/p>\n","protected":false},"excerpt":{"rendered":"Understanding Regression in Machine Learning\n","protected":false},"author":1,"featured_media":6800,"template":"","meta":{"om_disable_all_campaigns":false,"_monsterinsights_skip_tracking":false,"_monsterinsights_sitenote_active":false,"_monsterinsights_sitenote_note":"","_monsterinsights_sitenote_category":0,"web_stories_publisher_logo":935,"web_stories_poster":[],"web_stories_products":[],"footnotes":""},"web_story_category":[],"web_story_tag":[],"class_list":["post-6782","web-story","type-web-story","status-publish","has-post-thumbnail"],"yoast_head":"<!-- This site is optimized with the Yoast SEO Premium plugin v20.3 (Yoast SEO v27.3) - https:\/\/yoast.com\/product\/yoast-seo-premium-wordpress\/ -->\n<title>Understanding Regression in Machine Learning - 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