{"id":215690,"date":"2024-01-05T18:30:00","date_gmt":"2024-01-05T18:30:00","guid":{"rendered":"https:\/\/datascientest.com\/?p=215690"},"modified":"2023-12-28T14:42:09","modified_gmt":"2023-12-28T14:42:09","slug":"regression-lineaire-multiple-tout-savoir","status":"publish","type":"post","link":"https:\/\/datascientest.com\/regression-lineaire-multiple-tout-savoir","title":{"rendered":"R\u00e9gression lin\u00e9aire multiple : Qu&rsquo;est-ce que c&rsquo;est ? \u00c0 quoi \u00e7a sert ?"},"content":{"rendered":"\t\t<div data-elementor-type=\"wp-post\" data-elementor-id=\"215690\" class=\"elementor elementor-215690\" data-elementor-post-type=\"post\">\n\t\t\t\t\t\t\t<div class=\"elementor-element elementor-element-fbdd8d8 e-flex e-con-boxed e-con\" data-id=\"fbdd8d8\" data-element_type=\"container\" data-settings=\"{&quot;content_width&quot;:&quot;boxed&quot;}\">\n\t\t\t\t\t<div class=\"e-con-inner\">\n\t\t\t\t<div class=\"elementor-element elementor-element-fb43247 elementor-widget elementor-widget-heading\" data-id=\"fb43247\" data-element_type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t<style>\/*! elementor - v3.15.0 - 02-08-2023 *\/\n.elementor-heading-title{padding:0;margin:0;line-height:1}.elementor-widget-heading .elementor-heading-title[class*=elementor-size-]>a{color:inherit;font-size:inherit;line-height:inherit}.elementor-widget-heading .elementor-heading-title.elementor-size-small{font-size:15px}.elementor-widget-heading .elementor-heading-title.elementor-size-medium{font-size:19px}.elementor-widget-heading .elementor-heading-title.elementor-size-large{font-size:29px}.elementor-widget-heading .elementor-heading-title.elementor-size-xl{font-size:39px}.elementor-widget-heading .elementor-heading-title.elementor-size-xxl{font-size:59px}<\/style><h2 class=\"elementor-heading-title elementor-size-default\">Plut\u00f4t que d\u2019expliquer les relations entre deux variables, la r\u00e9gression lin\u00e9aire multiple \u00e9tablit des relations entre une variable et plusieurs variables explicatives. Cette approche multidimensionnelle permet d\u2019approfondir davantage les liens entre diff\u00e9rents jeux de donn\u00e9es, tout en r\u00e9duisant le risque d\u2019erreur d\u2019interpr\u00e9tation. D\u00e9couvrez plus en d\u00e9tail le mod\u00e8le de r\u00e9gression lin\u00e9aire multiple, ses traductions math\u00e9matiques et ses avantages.<\/h2>\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t<div class=\"elementor-element elementor-element-cf80f2e e-flex e-con-boxed e-con\" data-id=\"cf80f2e\" data-element_type=\"container\" data-settings=\"{&quot;content_width&quot;:&quot;boxed&quot;}\">\n\t\t\t\t\t<div class=\"e-con-inner\">\n\t\t\t\t<div class=\"elementor-element elementor-element-1f11592 elementor-widget elementor-widget-heading\" data-id=\"1f11592\" data-element_type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t<h3 class=\"elementor-heading-title elementor-size-default\">C\u2019est quoi la r\u00e9gression lin\u00e9aire multiple ?<\/h3>\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-44df166 elementor-widget elementor-widget-heading\" data-id=\"44df166\" data-element_type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t<h4 class=\"elementor-heading-title elementor-size-medium\">D\u00e9finition<\/h4>\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-9764e5e elementor-widget elementor-widget-text-editor\" data-id=\"9764e5e\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t<style>\/*! elementor - v3.15.0 - 02-08-2023 *\/\n.elementor-widget-text-editor.elementor-drop-cap-view-stacked .elementor-drop-cap{background-color:#69727d;color:#fff}.elementor-widget-text-editor.elementor-drop-cap-view-framed .elementor-drop-cap{color:#69727d;border:3px solid;background-color:transparent}.elementor-widget-text-editor:not(.elementor-drop-cap-view-default) .elementor-drop-cap{margin-top:8px}.elementor-widget-text-editor:not(.elementor-drop-cap-view-default) .elementor-drop-cap-letter{width:1em;height:1em}.elementor-widget-text-editor .elementor-drop-cap{float:left;text-align:center;line-height:1;font-size:50px}.elementor-widget-text-editor .elementor-drop-cap-letter{display:inline-block}<\/style>\t\t\t\t<p><span style=\"font-weight: 400;\">Avant de comprendre la r\u00e9gression lin\u00e9aire multiple (\u00e9galement appel\u00e9 r\u00e9gression lin\u00e9aire multidimensionnelle ou RLM), il convient de red\u00e9finir les bases. Et plus pr\u00e9cis\u00e9ment, la<\/span><b> r\u00e9gression lin\u00e9aire. <\/b><span style=\"font-weight: 400;\">Cet <a href=\"https:\/\/datascientest.com\/algorithme-de-classification-definition-et-principaux-modeles\">algorithme de classification<\/a> a pour objectif d\u2019\u00e9tablir des relations entre une variable \u00e0 expliquer Y (que l\u2019on appelle variable d\u00e9pendante ou variable r\u00e9ponse) et une variable explicative X (que l\u2019on appelle variable ind\u00e9pendante).<\/span><\/p><p><span style=\"font-weight: 400;\">Ce mod\u00e8le prend forme sur un <a href=\"https:\/\/datascientest.com\/scatter-plot\">nuage de point<\/a> o\u00f9 X se trouve sur l\u2019axe des ordonn\u00e9es et o\u00f9 Y se trouve sur l\u2019axe des abscisses. Dans ce cas, la r\u00e9gression lin\u00e9aire doit d\u00e9terminer une droite capable de passer au plus pr\u00e8s des points du nuage. Pour cela, on utilise l<\/span><span style=\"font-weight: 400;\">a m\u00e9thode des moindres carr\u00e9s (ou MCO pour moindres carr\u00e9s ordinaires).<\/span><span style=\"font-weight: 400;\">Cette droite d\u00e9termine ainsi la relation entre X et Y.<\/span><\/p><p><span style=\"font-weight: 400;\">\u00c0 partir de l\u00e0, il est possible d\u2019expliquer une variable d\u00e9pendante Y \u00e0 partir d\u2019une variable ind\u00e9pendante X (c\u2019est la r\u00e9gression lin\u00e9aire simple) ou d<\/span><b>\u2019expliquer la variable d\u00e9pendante Y \u00e0 partir de plusieurs variables ind\u00e9pendantes X<\/b><span style=\"font-weight: 400;\"> (au moins 2). C\u2019est justement \u00e7a la r\u00e9gression lin\u00e9aire multiple. L\u2019\u00e9tablissement de relations entre diff\u00e9rentes variables permet ainsi de <a href=\"https:\/\/datascientest.com\/quest-ce-que-cest-le-predictive-modelling\">r\u00e9aliser des pr\u00e9dictions<\/a> avec un minimum d&rsquo;erreurs.<\/span><\/p><p><span style=\"font-weight: 400;\">Quel que soit le mod\u00e8le, la variable d\u00e9pendante est toujours de type num\u00e9rique continue, contrairement aux variables ind\u00e9pendantes qui peuvent \u00eatre continues ou cat\u00e9gorielles (mais toujours num\u00e9riques).<\/span><\/p>\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-8a0f006 elementor-widget elementor-widget-heading\" data-id=\"8a0f006\" data-element_type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t<h4 class=\"elementor-heading-title elementor-size-medium\">Traduction math\u00e9matique<\/h4>\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-47355a9 elementor-widget elementor-widget-text-editor\" data-id=\"47355a9\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<p><span style=\"font-weight: 400;\">La r\u00e9gression lin\u00e9aire multiple peut \u00eatre utilis\u00e9e d\u00e8s lors que vous disposez de ce type de jeu de donn\u00e9es :<\/span><\/p>\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-db7de00 elementor-widget elementor-widget-html\" data-id=\"db7de00\" data-element_type=\"widget\" data-widget_type=\"html.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t<style type=\"text\/css\">\r\n.tg  {border-collapse:collapse;border-spacing:0;}\r\n.tg td{border-color:black;border-style:solid;border-width:1px;font-family:Arial, sans-serif;font-size:14px;\r\n  overflow:hidden;padding:10px 5px;word-break:normal;}\r\n.tg th{border-color:black;border-style:solid;border-width:1px;font-family:Arial, sans-serif;font-size:14px;\r\n  font-weight:normal;overflow:hidden;padding:10px 5px;word-break:normal;}\r\n.tg .tg-gg21{font-family:Tahoma, Geneva, sans-serif !important;font-size:18px;text-align:left;vertical-align:top}\r\n.tg .tg-y5vs{font-family:Tahoma, Geneva, sans-serif !important;font-size:18px;font-weight:bold;text-align:left;vertical-align:top}\r\n<\/style>\r\n<table class=\"tg\" style=\"undefined;table-layout: fixed; width: 450px\">\r\n<colgroup>\r\n<col style=\"width: 75px\">\r\n<col style=\"width: 75px\">\r\n<col style=\"width: 75px\">\r\n<col style=\"width: 75px\">\r\n<col style=\"width: 75px\">\r\n<col style=\"width: 75px\">\r\n<\/colgroup>\r\n<thead>\r\n  <tr>\r\n    <th class=\"tg-gg21\"><\/th>\r\n    <th class=\"tg-y5vs\"><span style=\"font-style:normal;text-decoration:none;color:#000;background-color:transparent\">Y<\/span><\/th>\r\n    <th class=\"tg-y5vs\"><span style=\"font-style:normal;text-decoration:none;color:#000;background-color:transparent\">X1<\/span><\/th>\r\n    <th class=\"tg-y5vs\"><span style=\"font-style:normal;text-decoration:none;color:#000;background-color:transparent\">X2<\/span><\/th>\r\n    <th class=\"tg-y5vs\"><span style=\"font-style:normal;text-decoration:none;color:#000;background-color:transparent\">\u2026<\/span><\/th>\r\n    <th class=\"tg-y5vs\"><span style=\"font-style:normal;text-decoration:none;color:#000;background-color:transparent\">Xn<\/span><\/th>\r\n  <\/tr>\r\n<\/thead>\r\n<tbody>\r\n  <tr>\r\n    <td class=\"tg-y5vs\"><span style=\"font-style:normal;text-decoration:none;color:#000;background-color:transparent\">1<\/span><\/td>\r\n    <td class=\"tg-gg21\"><span style=\"font-weight:400;font-style:normal;text-decoration:none;color:#000;background-color:transparent\">15<\/span><\/td>\r\n    <td class=\"tg-gg21\"><span style=\"font-weight:400;font-style:normal;text-decoration:none;color:#000;background-color:transparent\">54<\/span><\/td>\r\n    <td class=\"tg-gg21\"><span style=\"font-weight:400;font-style:normal;text-decoration:none;color:#000;background-color:transparent\">\u2026<\/span><\/td>\r\n    <td class=\"tg-gg21\"><span style=\"font-weight:400;font-style:normal;text-decoration:none;color:#000;background-color:transparent\">\u2026<\/span><\/td>\r\n    <td class=\"tg-gg21\"><span style=\"font-weight:400;font-style:normal;text-decoration:none;color:#000;background-color:transparent\">\u2026<\/span><\/td>\r\n  <\/tr>\r\n  <tr>\r\n    <td class=\"tg-y5vs\"><span style=\"font-style:normal;text-decoration:none;color:#000;background-color:transparent\">2<\/span><\/td>\r\n    <td class=\"tg-gg21\"><span style=\"font-weight:400;font-style:normal;text-decoration:none;color:#000;background-color:transparent\">58<\/span><\/td>\r\n    <td class=\"tg-gg21\"><span style=\"font-weight:400;font-style:normal;text-decoration:none;color:#000;background-color:transparent\">65<\/span><\/td>\r\n    <td class=\"tg-gg21\"><span style=\"font-weight:400;font-style:normal;text-decoration:none;color:#000;background-color:transparent\">\u2026<\/span><\/td>\r\n    <td class=\"tg-gg21\"><span style=\"font-weight:400;font-style:normal;text-decoration:none;color:#000;background-color:transparent\">\u2026<\/span><\/td>\r\n    <td class=\"tg-gg21\"><span style=\"font-weight:400;font-style:normal;text-decoration:none;color:#000;background-color:transparent\">\u2026<\/span><\/td>\r\n  <\/tr>\r\n  <tr>\r\n    <td class=\"tg-y5vs\"><span style=\"font-style:normal;text-decoration:none;color:#000;background-color:transparent\">\u2026<\/span><\/td>\r\n    <td class=\"tg-gg21\"><span style=\"font-weight:400;font-style:normal;text-decoration:none;color:#000;background-color:transparent\">\u2026<\/span><\/td>\r\n    <td class=\"tg-gg21\"><span style=\"font-weight:400;font-style:normal;text-decoration:none;color:#000;background-color:transparent\">\u2026<\/span><\/td>\r\n    <td class=\"tg-gg21\"><span style=\"font-weight:400;font-style:normal;text-decoration:none;color:#000;background-color:transparent\">\u2026<\/span><\/td>\r\n    <td class=\"tg-gg21\"><span style=\"font-weight:400;font-style:normal;text-decoration:none;color:#000;background-color:transparent\">\u2026<\/span><\/td>\r\n    <td class=\"tg-gg21\"><span style=\"font-weight:400;font-style:normal;text-decoration:none;color:#000;background-color:transparent\">\u2026<\/span><\/td>\r\n  <\/tr>\r\n  <tr>\r\n    <td class=\"tg-y5vs\"><span style=\"font-style:normal;text-decoration:none;color:#000;background-color:transparent\">n<\/span><\/td>\r\n    <td class=\"tg-gg21\"><span style=\"font-weight:400;font-style:normal;text-decoration:none;color:#000;background-color:transparent\">\u2026<\/span><\/td>\r\n    <td class=\"tg-gg21\"><span style=\"font-weight:400;font-style:normal;text-decoration:none;color:#000;background-color:transparent\">\u2026<\/span><\/td>\r\n    <td class=\"tg-gg21\"><span style=\"font-weight:400;font-style:normal;text-decoration:none;color:#000;background-color:transparent\">\u2026<\/span><\/td>\r\n    <td class=\"tg-gg21\"><span style=\"font-weight:400;font-style:normal;text-decoration:none;color:#000;background-color:transparent\">\u2026<\/span><\/td>\r\n    <td class=\"tg-gg21\"><span style=\"font-weight:400;font-style:normal;text-decoration:none;color:#000;background-color:transparent\">\u2026<\/span><\/td>\r\n  <\/tr>\r\n<\/tbody>\r\n<\/table>\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-f4fdfea elementor-widget elementor-widget-text-editor\" data-id=\"f4fdfea\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<span style=\"font-weight: 400;\">\u00c0 partir de ce tableau, la RLM se pr\u00e9sente sous la forme suivante :<\/span>\n<p style=\"text-align: left; padding-left: 40px;\"><b>yi = \u03b20 + \u03b21xi1 +\u2026+ \u03b2pxip + \u03f5i<\/b><\/p>\n<span style=\"font-weight: 400;\">O\u00f9<\/span>\n<ul>\n \t<li style=\"font-weight: 400;\" aria-level=\"1\">yi =\u00a0 les variables d\u00e9pendantes ;\u00a0<\/span><\/li>\n \t<li style=\"font-weight: 400;\" aria-level=\"1\">i = l\u2019indice des observations ;\u00a0<\/span><\/li>\n \t<li style=\"font-weight: 400;\" aria-level=\"1\">xij = les valeurs observ\u00e9es des variables ind\u00e9pendantes ;\u00a0<\/span><\/li>\n \t<li style=\"font-weight: 400;\" aria-level=\"1\">\u03b2p = les param\u00e8tres inconnus (\u00e9galement parfois appel\u00e9s \u201cpentes partielles\u201d) ; <\/span><\/li>\n \t<li style=\"font-weight: 400;\" aria-level=\"1\">\u03f5i = les r\u00e9sidus (autrement dit, l\u2019erreur de pr\u00e9diction<span>).<\/span><\/li>\n<\/ul>\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-8e98632 elementor-widget elementor-widget-text-editor\" data-id=\"8e98632\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<p><span style=\"font-weight: 400;\">Comme toute r\u00e9gression lin\u00e9aire, la r\u00e9gression multiple se formalise \u00e0 travers un nuage de point. Mais contrairement \u00e0 la r\u00e9gression simple qui se projette sur un plan graphique en deux dimensions, la r\u00e9gression lin\u00e9aire multiple se projette sur un <\/span><b>graphique \u00e0 plusieurs dimensions<\/b><span style=\"font-weight: 400;\">. C\u2019est cela qui permettra de mod\u00e9liser les diff\u00e9rentes variables explicatives. <\/span><\/p>\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-ff99d47 elementor-widget elementor-widget-image\" data-id=\"ff99d47\" data-element_type=\"widget\" data-widget_type=\"image.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t<style>\/*! elementor - v3.15.0 - 02-08-2023 *\/\n.elementor-widget-image{text-align:center}.elementor-widget-image a{display:inline-block}.elementor-widget-image a img[src$=\".svg\"]{width:48px}.elementor-widget-image img{vertical-align:middle;display:inline-block}<\/style>\t\t\t\t\t\t\t\t\t\t\t\t<img decoding=\"async\" width=\"900\" height=\"500\" src=\"https:\/\/datascientest.com\/wp-content\/uploads\/2023\/09\/Regression-Lineaire-Multiple2.jpg\" class=\"attachment-full size-full wp-image-215703\" alt=\"\" srcset=\"https:\/\/datascientest.com\/wp-content\/uploads\/2023\/09\/Regression-Lineaire-Multiple2.jpg 900w, https:\/\/datascientest.com\/wp-content\/uploads\/2023\/09\/Regression-Lineaire-Multiple2-300x167.jpg 300w, https:\/\/datascientest.com\/wp-content\/uploads\/2023\/09\/Regression-Lineaire-Multiple2-768x427.jpg 768w\" sizes=\"(max-width: 900px) 100vw, 900px\" \/>\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-cb7dd48 elementor-align-center button-principale elementor-widget elementor-widget-button\" data-id=\"cb7dd48\" data-element_type=\"widget\" data-widget_type=\"button.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<div class=\"elementor-button-wrapper\">\n\t\t\t<a class=\"elementor-button elementor-button-link elementor-size-sm elementor-animation-grow\" href=\"https:\/\/datascientest.com\/formation-data-scientist\">\n\t\t\t\t\t\t<span class=\"elementor-button-content-wrapper\">\n\t\t\t\t\t\t<span class=\"elementor-button-text\">Ma\u00eetriser la r\u00e9grassion lin\u00e9aire multiple<\/span>\n\t\t<\/span>\n\t\t\t\t\t<\/a>\n\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t<div class=\"elementor-element elementor-element-6cbcb1b e-flex e-con-boxed e-con\" data-id=\"6cbcb1b\" data-element_type=\"container\" data-settings=\"{&quot;content_width&quot;:&quot;boxed&quot;}\">\n\t\t\t\t\t<div class=\"e-con-inner\">\n\t\t\t\t<div class=\"elementor-element elementor-element-9dc4a51 elementor-widget elementor-widget-heading\" data-id=\"9dc4a51\" data-element_type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t<h3 class=\"elementor-heading-title elementor-size-default\">Pourquoi utiliser la r\u00e9gression lin\u00e9aire multidimensionnelle ?<\/h3>\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-2948a2e elementor-widget elementor-widget-heading\" data-id=\"2948a2e\" data-element_type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t<h4 class=\"elementor-heading-title elementor-size-medium\">R\u00e9aliser des pr\u00e9dictions<\/h4>\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-eec77c3 elementor-widget elementor-widget-text-editor\" data-id=\"eec77c3\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<p><span style=\"font-weight: 400;\">En identifiant des liens de corr\u00e9lation entre un r\u00e9sultat (la variable d\u00e9pendante) et plusieurs variables explicatives et ind\u00e9pendantes, la r\u00e9gression lin\u00e9aire multiple permet de <\/span><b>r\u00e9aliser des pr\u00e9dictions et de d\u00e9gager des insights.\u00a0<\/b><\/p><p><span style=\"font-weight: 400;\">C\u2019est pourquoi, cette m\u00e9thode math\u00e9matique est utilis\u00e9e dans de nombreux domaines. D\u00e9couvrons quelques cas d\u2019usages :\u00a0<\/span><\/p><ul><li style=\"font-weight: 400;\" aria-level=\"1\"><b>Les performances commerciales<\/b><span style=\"font-weight: 400;\"> : les entreprises peuvent pr\u00e9dire les ventes d\u2019un produit en utilisant les diff\u00e9rentes caract\u00e9ristiques de l\u2019acheteur type, comme son \u00e2ge, son niveau de salaire, sa localisation g\u00e9ographique, etc.\u00a0<\/span><\/li><li style=\"font-weight: 400;\" aria-level=\"1\"><b>Les pr\u00e9visions m\u00e9t\u00e9orologiques<\/b><span style=\"font-weight: 400;\"> : les m\u00e9t\u00e9orologues peuvent pr\u00e9dire le temps qu\u2019il fera dans la semaine en fonction de la temp\u00e9rature de l\u2019air, le degr\u00e9 d\u2019hygrom\u00e9trie, la pression atmosph\u00e9rique, etc.\u00a0<\/span><\/li><li style=\"font-weight: 400;\" aria-level=\"1\"><b>La m\u00e9decine<\/b><span style=\"font-weight: 400;\"> : les professionnels de sant\u00e9 peuvent anticiper la propagation d\u2019un virus dans une r\u00e9gion selon le nombre de personnes infect\u00e9es, la rapidit\u00e9 de la contamination, la consommation de tel ou tel aliment, les conditions m\u00e9t\u00e9orologiques, etc. <\/span><\/li><li style=\"font-weight: 400;\" aria-level=\"1\"><b>La bourse <\/b><span>: les analystes financiers peuvent pr\u00e9dire le cours d\u2019une action selon la sant\u00e9 financi\u00e8re de l\u2019entreprise, son actualit\u00e9, la conjoncture \u00e9conomique, etc.<\/span><\/li><\/ul>\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-790f40b elementor-widget elementor-widget-heading\" data-id=\"790f40b\" data-element_type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t<h4 class=\"elementor-heading-title elementor-size-medium\">Limiter la confusion entre des variables explicatives<\/h4>\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-5e23a90 elementor-widget elementor-widget-text-editor\" data-id=\"5e23a90\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<p><span style=\"font-weight: 400;\">Outre la r\u00e9alisation de pr\u00e9diction, la r\u00e9gression lin\u00e9aire multiple permet \u00e9galement de <\/span><b>pallier les limites de la r\u00e9gression lin\u00e9aire simple.<\/b><span style=\"font-weight: 400;\"> En effet, dans certains cas, il peut y avoir un lien apparent entre une variable \u00e0 expliquer et une variable explicative. Pour autant, ce lien ne semble pas logique.\u00a0<\/span><\/p><p><span style=\"font-weight: 400;\">Par exemple, il y a une forte corr\u00e9lation entre la consommation de bonbons \u00e0 la menthe et les capacit\u00e9s respiratoires. Ainsi, les capacit\u00e9s respiratoires diminuent \u00e0 mesure que la consommation de bonbons \u00e0 la menthe augmente. Cela signifie-t-il que la consommation de bonbons \u00e0 la menthe explique ces faiblesses respiratoires ? Non, il y a un autre facteur.\u00a0<\/span><\/p><p><span style=\"font-weight: 400;\">L\u00e0 encore, on constate qu\u2019il y a une corr\u00e9lation nette entre la consommation de bonbons \u00e0 la menthe et le tabagisme. Mais \u00e9galement entre le tabagisme et les capacit\u00e9s respiratoires.\u00a0<\/span><\/p><p><span style=\"font-weight: 400;\">Dans cette hypoth\u00e8se, la variable consommation de bonbons \u00e0 la menthe est li\u00e9e \u00e0 la fois \u00e0 la variable r\u00e9ponse (capacit\u00e9 respiratoire) et \u00e0 la variable explicative (tabagisme). Elle devient alors <\/span><b>facteur de confusion.\u00a0<\/b><\/p><p><span style=\"font-weight: 400;\">Pour d\u00e9celer cette confusion, l\u2019utilisation de la r\u00e9gression lin\u00e9aire simple s\u2019av\u00e8re insuffisante. \u00c0 la place, il convient d\u2019utiliser la r\u00e9gression lin\u00e9aire multiple. Cette derni\u00e8re permet ainsi de d\u00e9terminer la relation entre la variable et les variables explicatives. Et ce, en<\/span><b> tenant compte de toutes ces variables explicatives. <\/b><\/p>\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t<div class=\"elementor-element elementor-element-9c6d88d e-flex e-con-boxed e-con\" data-id=\"9c6d88d\" data-element_type=\"container\" data-settings=\"{&quot;content_width&quot;:&quot;boxed&quot;}\">\n\t\t\t\t\t<div class=\"e-con-inner\">\n\t\t\t\t<div class=\"elementor-element elementor-element-8dd7462 elementor-widget elementor-widget-heading\" data-id=\"8dd7462\" data-element_type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t<h3 class=\"elementor-heading-title elementor-size-default\">R\u00e9gression lin\u00e9aire et Machine Learning<\/h3>\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-635f37c elementor-widget elementor-widget-text-editor\" data-id=\"635f37c\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<p><span style=\"font-weight: 400;\">En plus d\u2019expliquer une variable en fonction de plusieurs donn\u00e9es ind\u00e9pendantes les unes des autres, la r\u00e9gression lin\u00e9aire multiple est aussi <\/span><b>capable d&rsquo;assimiler de nouvelles r\u00e8gles par elle-m\u00eame.<\/b><span style=\"font-weight: 400;\"> \u00c0 ce titre, cet outil math\u00e9matique est un incontournable de l&rsquo;<a href=\"https:\/\/datascientest.com\/intelligence-artificielle-definition\">intelligence artificielle<\/a>. L\u2019id\u00e9e est alors de commencer par une phase d\u2019apprentissage avec des nuages de points d&rsquo;entra\u00eenement. Ce qui permet d\u2019obtenir un mod\u00e8le de <a href=\"https:\/\/datascientest.com\/machine-learning-tout-savoir\">machine learning<\/a> performant capable d\u2019\u00e9tablir avec pr\u00e9cision les relations entre une variable \u00e0 expliquer et d\u2019autres variables explicatives.<\/span><\/p><p><span style=\"font-weight: 400;\">Mais pour d\u00e9velopper ces mod\u00e8les et interpr\u00e9ter les r\u00e9sultats obtenus, il est n\u00e9cessaire de suivre une formation approfondie. C\u2019est justement possible avec DataScientest. \u00c0 travers notre <a href=\"https:\/\/datascientest.com\/formation-data-scientist\">formation en science des donn\u00e9es<\/a>, vous apprendrez tout ce qu\u2019il faut savoir sur la r\u00e9gression lin\u00e9aire multiple et tous les autres outils de Machine Learning. Rejoignez-nous !<\/span><\/p>\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-d2dde04 elementor-widget elementor-widget-image\" data-id=\"d2dde04\" data-element_type=\"widget\" data-widget_type=\"image.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<img decoding=\"async\" width=\"900\" height=\"500\" src=\"https:\/\/datascientest.com\/wp-content\/uploads\/2023\/09\/Regression-Lineaire-Multiple1.jpg\" class=\"attachment-full size-full wp-image-215702\" alt=\"\" srcset=\"https:\/\/datascientest.com\/wp-content\/uploads\/2023\/09\/Regression-Lineaire-Multiple1.jpg 900w, https:\/\/datascientest.com\/wp-content\/uploads\/2023\/09\/Regression-Lineaire-Multiple1-300x167.jpg 300w, https:\/\/datascientest.com\/wp-content\/uploads\/2023\/09\/Regression-Lineaire-Multiple1-768x427.jpg 768w\" sizes=\"(max-width: 900px) 100vw, 900px\" \/>\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-e0f5a41 elementor-align-center button-principale elementor-widget elementor-widget-button\" data-id=\"e0f5a41\" data-element_type=\"widget\" data-widget_type=\"button.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<div class=\"elementor-button-wrapper\">\n\t\t\t<a class=\"elementor-button elementor-button-link elementor-size-sm elementor-animation-grow\" href=\"https:\/\/datascientest.com\/formation-machine-learning-engineer\">\n\t\t\t\t\t\t<span class=\"elementor-button-content-wrapper\">\n\t\t\t\t\t\t<span class=\"elementor-button-text\">D\u00e9couvrir la formation en Machine Learning<\/span>\n\t\t<\/span>\n\t\t\t\t\t<\/a>\n\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t<div class=\"elementor-element elementor-element-9418fdf e-flex e-con-boxed e-con\" data-id=\"9418fdf\" data-element_type=\"container\" data-settings=\"{&quot;content_width&quot;:&quot;boxed&quot;}\">\n\t\t\t\t\t<div class=\"e-con-inner\">\n\t\t\t\t<div class=\"elementor-element elementor-element-e800101 elementor-widget elementor-widget-html\" data-id=\"e800101\" data-element_type=\"widget\" data-widget_type=\"html.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t<script type=\"application\/ld+json\">\r\n{\r\n  \"@context\": \"https:\/\/schema.org\",\r\n  \"@type\": \"FAQPage\",\r\n  \"mainEntity\": [{\r\n    \"@type\": \"Question\",\r\n    \"name\": \"C\u2019est quoi la r\u00e9gression lin\u00e9aire multiple ?\",\r\n    \"acceptedAnswer\": {\r\n      \"@type\": \"Answer\",\r\n      \"text\": \"Avant de comprendre la r\u00e9gression lin\u00e9aire multiple (\u00e9galement appel\u00e9 r\u00e9gression lin\u00e9aire multidimensionnelle ou RLM), il convient de red\u00e9finir les bases. Et plus pr\u00e9cis\u00e9ment, la r\u00e9gression lin\u00e9aire. Cet algorithme de classification a pour objectif d\u2019\u00e9tablir des relations entre une variable \u00e0 expliquer Y (que l\u2019on appelle variable d\u00e9pendante ou variable r\u00e9ponse) et une variable explicative X (que l\u2019on appelle variable ind\u00e9pendante).\"\r\n    }\r\n  },{\r\n    \"@type\": \"Question\",\r\n    \"name\": \"R\u00e9aliser des pr\u00e9dictions\",\r\n    \"acceptedAnswer\": {\r\n      \"@type\": \"Answer\",\r\n      \"text\": \"En identifiant des liens de corr\u00e9lation entre un r\u00e9sultat (la variable d\u00e9pendante) et plusieurs variables explicatives et ind\u00e9pendantes, la r\u00e9gression lin\u00e9aire multiple permet de r\u00e9aliser des pr\u00e9dictions et de d\u00e9gager des insights.\"\r\n    }\r\n  },{\r\n    \"@type\": \"Question\",\r\n    \"name\": \"R\u00e9gression lin\u00e9aire et Machine Learning\",\r\n    \"acceptedAnswer\": {\r\n      \"@type\": \"Answer\",\r\n      \"text\": \"En plus d\u2019expliquer une variable en fonction de plusieurs donn\u00e9es ind\u00e9pendantes les unes des autres, la r\u00e9gression lin\u00e9aire multiple est aussi capable d'assimiler de nouvelles r\u00e8gles par elle-m\u00eame. \u00c0 ce titre, cet outil math\u00e9matique est un incontournable de l'intelligence artificielle. L\u2019id\u00e9e est alors de commencer par une phase d\u2019apprentissage avec des nuages de points d'entra\u00eenement. Ce qui permet d\u2019obtenir un mod\u00e8le de machine learning performant capable d\u2019\u00e9tablir avec pr\u00e9cision les relations entre une variable \u00e0 expliquer et d\u2019autres variables explicatives.\"\r\n    }\r\n  }]\r\n}\r\n<\/script>\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t\t\t<\/div>\n\t\t","protected":false},"excerpt":{"rendered":"<p>Plut\u00f4t que d\u2019expliquer les relations entre deux variables, la r\u00e9gression lin\u00e9aire multiple \u00e9tablit des relations entre une variable et plusieurs variables explicatives. Cette approche multidimensionnelle permet d\u2019approfondir davantage les liens entre diff\u00e9rents jeux de donn\u00e9es, tout en r\u00e9duisant le risque d\u2019erreur d\u2019interpr\u00e9tation. D\u00e9couvrez plus en d\u00e9tail le mod\u00e8le de r\u00e9gression lin\u00e9aire multiple, ses traductions math\u00e9matiques [&hellip;]<\/p>\n","protected":false},"author":78,"featured_media":215692,"comment_status":"open","ping_status":"open","sticky":false,"template":"elementor_theme","format":"standard","meta":{"content-type":"","inline_featured_image":false},"categories":[2497],"tags":[],"yoast_head":"<!-- This site is optimized with the Yoast SEO Premium plugin v21.7 (Yoast SEO v21.7) - https:\/\/yoast.com\/wordpress\/plugins\/seo\/ -->\n<title>R\u00e9gression lin\u00e9aire multiple : Qu&#039;est-ce que c&#039;est ? \u00c0 quoi \u00e7a sert ?<\/title>\n<meta name=\"description\" content=\"La r\u00e9gression lin\u00e9aire multiple permet d\u2019expliquer les relations entre une variable d\u00e9pendante et plusieurs variables ind\u00e9pendantes. D\u00e9cryptage.\" \/>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/datascientest.com\/regression-lineaire-multiple-tout-savoir\" \/>\n<meta property=\"og:locale\" content=\"fr_FR\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"R\u00e9gression lin\u00e9aire multiple : Qu&#039;est-ce que c&#039;est ? \u00c0 quoi \u00e7a sert ?\" \/>\n<meta property=\"og:url\" content=\"https:\/\/datascientest.com\/regression-lineaire-multiple-tout-savoir\" \/>\n<meta property=\"og:site_name\" content=\"Formation Data Science | DataScientest.com\" \/>\n<meta property=\"article:published_time\" content=\"2024-01-05T18:30:00+00:00\" \/>\n<meta property=\"article:modified_time\" content=\"2023-12-28T14:42:09+00:00\" \/>\n<meta property=\"og:image\" content=\"https:\/\/datascientest.com\/wp-content\/uploads\/2023\/09\/Regression-Lineaire-Multiple.png\" \/>\n\t<meta property=\"og:image:width\" content=\"1200\" \/>\n\t<meta property=\"og:image:height\" content=\"600\" \/>\n\t<meta property=\"og:image:type\" content=\"image\/png\" \/>\n<meta name=\"author\" content=\"J\u00e9r\u00e9my Robert\" \/>\n<meta name=\"twitter:card\" content=\"summary_large_image\" \/>\n<meta name=\"twitter:label1\" content=\"\u00c9crit par\" \/>\n\t<meta name=\"twitter:data1\" content=\"J\u00e9r\u00e9my Robert\" \/>\n\t<meta name=\"twitter:label2\" content=\"Dur\u00e9e de lecture estim\u00e9e\" \/>\n\t<meta name=\"twitter:data2\" content=\"6 minutes\" \/>\n<script type=\"application\/ld+json\" class=\"yoast-schema-graph\">{\"@context\":\"https:\/\/schema.org\",\"@graph\":[{\"@type\":\"WebPage\",\"@id\":\"https:\/\/datascientest.com\/regression-lineaire-multiple-tout-savoir\",\"url\":\"https:\/\/datascientest.com\/regression-lineaire-multiple-tout-savoir\",\"name\":\"R\u00e9gression lin\u00e9aire multiple : Qu'est-ce que c'est ? \u00c0 quoi \u00e7a sert ?\",\"isPartOf\":{\"@id\":\"https:\/\/datascientest.com\/#website\"},\"datePublished\":\"2024-01-05T18:30:00+00:00\",\"dateModified\":\"2023-12-28T14:42:09+00:00\",\"author\":{\"@id\":\"https:\/\/datascientest.com\/#\/schema\/person\/7af2361c48e24e79a8aa2360e6e74925\"},\"description\":\"La r\u00e9gression lin\u00e9aire multiple permet d\u2019expliquer les relations entre une variable d\u00e9pendante et plusieurs variables ind\u00e9pendantes. 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Avant de rejoindre DataScientest, il a travaill\u00e9 en tant que Consultant Business Intelligence chez DEAPDATA, o\u00f9 il a g\u00e9r\u00e9 des projets dans les domaines de l'assurance, bancaire et industrie. Il a \u00e9galement \u00e9t\u00e9 Co-fondateur et pr\u00e9sident de Tripzer. En tant que consultant ind\u00e9pendant, J\u00e9r\u00e9my a propos\u00e9 des formations sur MicroStrategy pour divers niveaux professionnels. 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