{"id":66411,"date":"2021-05-31T21:42:13","date_gmt":"2021-05-31T20:42:13","guid":{"rendered":"https:\/\/datascientest.com\/?p=66411"},"modified":"2023-11-09T14:07:14","modified_gmt":"2023-11-09T14:07:14","slug":"tout-savoir-sur-scikit-learn","status":"publish","type":"post","link":"https:\/\/datascientest.com\/tout-savoir-sur-scikit-learn","title":{"rendered":"Scikit-Learn : D\u00e9couvrez la librairie Python d\u00e9di\u00e9 au Machine Learning"},"content":{"rendered":"\t\t<div data-elementor-type=\"wp-post\" data-elementor-id=\"66411\" class=\"elementor elementor-66411\" data-elementor-post-type=\"post\">\n\t\t\t\t\t\t\t\t\t<section class=\"elementor-section elementor-top-section elementor-element elementor-element-52608ad elementor-section-boxed elementor-section-height-default elementor-section-height-default\" data-id=\"52608ad\" data-element_type=\"section\">\n\t\t\t\t\t\t<div class=\"elementor-container elementor-column-gap-default\">\n\t\t\t\t\t<div class=\"elementor-column elementor-col-100 elementor-top-column elementor-element elementor-element-e398871\" data-id=\"e398871\" data-element_type=\"column\">\n\t\t\t<div class=\"elementor-widget-wrap elementor-element-populated\">\n\t\t\t\t\t\t\t\t<div class=\"elementor-element elementor-element-b71c7a7 elementor-widget elementor-widget-heading\" data-id=\"b71c7a7\" 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\">Si vous \u00e9tudiez des donn\u00e9es et que vous souhaitez en tirer de l\u2019information, vous devrez souvent traiter les donn\u00e9es, les modifier et surtout construire des mod\u00e8les capables d\u2019apprendre des sch\u00e9mas dans vos donn\u00e9es pour une probl\u00e9matique choisie. Beaucoup de librairies open source permettent aujourd\u2019hui de le faire, mais la plus connue d\u2019entre elles est s\u00fbrement Scikit-Learn.<\/h2>\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-ca5297b elementor-widget elementor-widget-heading\" data-id=\"ca5297b\" 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\">Qu\u2019est ce que Sckikit-Learn ?<\/h3>\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-a504ff1 elementor-widget elementor-widget-text-editor\" data-id=\"a504ff1\" 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>C\u2019est une <a href=\"https:\/\/datascientest.com\/python-tout-savoir\">librairie Python<\/a> qui donne acc\u00e8s \u00e0 des versions efficaces d\u2019un grand nombre d\u2019algorithmes courants. Elle offre \u00e9galement une API propre et uniformis\u00e9e. Par cons\u00e9quent, un des gros avantages de Scikit-Learn est qu&rsquo;une fois que vous avez compris l&rsquo;utilisation et la syntaxe de base de Scikit-Learn pour un type de mod\u00e8le, <strong>le passage \u00e0 un nouveau mod\u00e8le ou algorithme est tr\u00e8s simple<\/strong>. La librairie ne permet pas seulement de faire de la mod\u00e9lisation, elle peut assurer \u00e9galement des \u00e9tapes de preprocessing ce que nous verrons dans la suite de l\u2019article.<\/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-7a1fb80 elementor-widget elementor-widget-heading\" data-id=\"7a1fb80\" 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\">Histoire et objectif<\/h3>\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-f56097e elementor-widget elementor-widget-text-editor\" data-id=\"f56097e\" 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>Le projet a \u00e9t\u00e9 initialement lanc\u00e9 en 2007 par <strong>David Cournapeau<\/strong> puis tr\u00e8s vite de nombreux membres de la communaut\u00e9 scientifique Python se sont mobilis\u00e9s autour. Le projet a tr\u00e8s vite progress\u00e9 dans le cadre de travaux sur l\u2019imagerie fonctionnelle du cerveau men\u00e9s par l\u2019Inria. Ainsi en 2009 une premi\u00e8re version Scikit-Learn est sortie. Depuis, pas moins d\u2019une quarantaine de versions sont sorties pour arriver \u00e0 la version actuelle 0.24.1. Ce chiffre en dit beaucoup de l\u2019implication, du travail r\u00e9alis\u00e9 sur le projet par des d\u00e9veloppeurs \u00e0 travers le monde, chaque version am\u00e9liorant ou ajoutant de nouvelles m\u00e9thodes statistiques innovantes.<\/p><p>D\u00e8s le d\u00e9part l&rsquo;objectif \u00e9tait ambitieux : faire en sorte que la librairie s\u2019utilise facilement sur plusieurs plateformes et la nourrir d\u2019une documentation exhaustive avec des exemples concrets sur chaque outil d\u00e9velopp\u00e9. Aujourd\u2019hui Scikit-Learn fait partie des librairies les plus populaires sur Github. De par les objectifs fix\u00e9s au d\u00e9but du projet, l\u2019une des forces de Scikit-Learn est sa flexibilit\u00e9 et la facilit\u00e9 avec laquelle vous pouvez l\u2019utiliser sur un grand nombre de probl\u00e9matiques comme par exemple de la segmentation client, de la recommandation de produits, de la d\u00e9tection de fraude&#8230;<\/p><p>Enfin, il est important de noter que Scikit-Learn est un projet open source disponible pour tous sous <b>licence BSD<\/b>. Sur le site de la librairie vous trouverez une documentation tr\u00e8s pr\u00e9cise des m\u00e9thodes statistiques disponibles avec des exemples pour comprendre, mais aussi des cas pratiques pour comparer les m\u00e9thodes entre elles et mieux les appr\u00e9hender.<\/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-14734e3 elementor-align-center button-principale elementor-widget elementor-widget-button\" data-id=\"14734e3\" 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\/formations-data\">\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\">Apprendre \u00e0 utiliser Scikit-Learn<\/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<div class=\"elementor-element elementor-element-4795166 elementor-widget elementor-widget-heading\" data-id=\"4795166\" 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\">Nos cheat sheets<\/h3>\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-5614a0d gallery-spacing-custom elementor-widget elementor-widget-image-gallery\" data-id=\"5614a0d\" data-element_type=\"widget\" data-widget_type=\"image-gallery.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t<style>.elementor-image-gallery .gallery-item{display:inline-block;text-align:center;vertical-align:top;width:100%;max-width:100%;margin:0 auto}.elementor-image-gallery .gallery-item img{margin:0 auto}.elementor-image-gallery .gallery-item .gallery-caption{margin:0}.elementor-image-gallery figure img{display:block}.elementor-image-gallery figure figcaption{width:100%}.gallery-spacing-custom .elementor-image-gallery .gallery-icon{padding:0}@media (min-width:768px){.elementor-image-gallery .gallery-columns-2 .gallery-item{max-width:50%}.elementor-image-gallery .gallery-columns-3 .gallery-item{max-width:33.33%}.elementor-image-gallery .gallery-columns-4 .gallery-item{max-width:25%}.elementor-image-gallery .gallery-columns-5 .gallery-item{max-width:20%}.elementor-image-gallery .gallery-columns-6 .gallery-item{max-width:16.666%}.elementor-image-gallery .gallery-columns-7 .gallery-item{max-width:14.28%}.elementor-image-gallery .gallery-columns-8 .gallery-item{max-width:12.5%}.elementor-image-gallery .gallery-columns-9 .gallery-item{max-width:11.11%}.elementor-image-gallery .gallery-columns-10 .gallery-item{max-width:10%}}@media (min-width:480px) and (max-width:767px){.elementor-image-gallery .gallery.gallery-columns-2 .gallery-item,.elementor-image-gallery .gallery.gallery-columns-3 .gallery-item,.elementor-image-gallery .gallery.gallery-columns-4 .gallery-item,.elementor-image-gallery .gallery.gallery-columns-5 .gallery-item,.elementor-image-gallery .gallery.gallery-columns-6 .gallery-item,.elementor-image-gallery .gallery.gallery-columns-7 .gallery-item,.elementor-image-gallery .gallery.gallery-columns-8 .gallery-item,.elementor-image-gallery .gallery.gallery-columns-9 .gallery-item,.elementor-image-gallery .gallery.gallery-columns-10 .gallery-item{max-width:50%}}@media (max-width:479px){.elementor-image-gallery .gallery.gallery-columns-2 .gallery-item,.elementor-image-gallery .gallery.gallery-columns-3 .gallery-item,.elementor-image-gallery .gallery.gallery-columns-4 .gallery-item,.elementor-image-gallery .gallery.gallery-columns-5 .gallery-item,.elementor-image-gallery .gallery.gallery-columns-6 .gallery-item,.elementor-image-gallery .gallery.gallery-columns-7 .gallery-item,.elementor-image-gallery .gallery.gallery-columns-8 .gallery-item,.elementor-image-gallery .gallery.gallery-columns-9 .gallery-item,.elementor-image-gallery .gallery.gallery-columns-10 .gallery-item{max-width:100%}}<\/style>\t\t<div class=\"elementor-image-gallery\">\n\t\t\t<div id='gallery-1' class='gallery galleryid-66411 gallery-columns-4 gallery-size-thumbnail'><figure class='gallery-item'>\n\t\t\t<div class='gallery-icon landscape'>\n\t\t\t\t<a data-elementor-open-lightbox=\"yes\" data-elementor-lightbox-slideshow=\"5614a0d\" data-elementor-lightbox-title=\"CheatSheet Processing\" data-e-action-hash=\"#elementor-action%3Aaction%3Dlightbox%26settings%3DeyJpZCI6NzMzOTMsInVybCI6Imh0dHBzOlwvXC9kYXRhc2NpZW50ZXN0LmNvbVwvd3AtY29udGVudFwvdXBsb2Fkc1wvMjAyMVwvMDZcL0NoZWF0U2hlZXQtU2Npa2l0LTEucG5nIiwic2xpZGVzaG93IjoiNTYxNGEwZCJ9\" href='https:\/\/datascientest.com\/wp-content\/uploads\/2021\/06\/CheatSheet-Scikit-1.png'><img width=\"150\" height=\"137\" src=\"https:\/\/datascientest.com\/wp-content\/uploads\/2021\/06\/CheatSheet-Scikit-1.png\" class=\"attachment-thumbnail size-thumbnail\" alt=\"CheatSheet Processing\" decoding=\"async\" aria-describedby=\"gallery-1-73393\" srcset=\"https:\/\/datascientest.com\/wp-content\/uploads\/2021\/06\/CheatSheet-Scikit-1.png 10711w, https:\/\/datascientest.com\/wp-content\/uploads\/2021\/06\/CheatSheet-Scikit-1-300x274.png 300w, https:\/\/datascientest.com\/wp-content\/uploads\/2021\/06\/CheatSheet-Scikit-1-768x700.png 768w\" sizes=\"(max-width: 150px) 100vw, 150px\" \/><\/a>\n\t\t\t<\/div>\n\t\t\t\t<figcaption class='wp-caption-text gallery-caption' id='gallery-1-73393'>\n\t\t\t\tProcessing\n\t\t\t\t<\/figcaption><\/figure><figure class='gallery-item'>\n\t\t\t<div class='gallery-icon portrait'>\n\t\t\t\t<a data-elementor-open-lightbox=\"yes\" data-elementor-lightbox-slideshow=\"5614a0d\" data-elementor-lightbox-title=\"CheatSheet Apprentissage Non Supervise\u0301\" data-e-action-hash=\"#elementor-action%3Aaction%3Dlightbox%26settings%3DeyJpZCI6NzMzNzksInVybCI6Imh0dHBzOlwvXC9kYXRhc2NpZW50ZXN0LmNvbVwvd3AtY29udGVudFwvdXBsb2Fkc1wvMjAyMVwvMDZcL0NoZWF0U2hlZXQtQXBwcmVudGlzc2FnZS1Ob24tU3VwZXJ2aXNlXHUwMzAxLnBuZyIsInNsaWRlc2hvdyI6IjU2MTRhMGQifQ%3D%3D\" href='https:\/\/datascientest.com\/wp-content\/uploads\/2021\/06\/CheatSheet-Apprentissage-Non-Supervise\u0301.png'><img width=\"150\" height=\"150\" src=\"https:\/\/datascientest.com\/wp-content\/uploads\/2021\/06\/CheatSheet-Apprentissage-Non-Supervise\u0301-150x150.png\" class=\"attachment-thumbnail size-thumbnail\" alt=\"CheatSheet Apprentissage Non Supervise\u0301\" decoding=\"async\" aria-describedby=\"gallery-1-73379\" \/><\/a>\n\t\t\t<\/div>\n\t\t\t\t<figcaption class='wp-caption-text gallery-caption' id='gallery-1-73379'>\n\t\t\t\tApprentissage Non Supervise\u0301\n\t\t\t\t<\/figcaption><\/figure><figure class='gallery-item'>\n\t\t\t<div class='gallery-icon portrait'>\n\t\t\t\t<a data-elementor-open-lightbox=\"yes\" data-elementor-lightbox-slideshow=\"5614a0d\" data-elementor-lightbox-title=\"CheatSheet Apprentissage Supervis\u00e9\" data-e-action-hash=\"#elementor-action%3Aaction%3Dlightbox%26settings%3DeyJpZCI6Njg3MjcsInVybCI6Imh0dHBzOlwvXC9kYXRhc2NpZW50ZXN0LmNvbVwvd3AtY29udGVudFwvdXBsb2Fkc1wvMjAyMFwvMTJcL0xhcHByZW50aXNzYWdlLXN1cGVydmlzZVx1MDMwMS1hdmVjLXNjaWtpdC1sZWFybi1zY2FsZWQuanBnIiwic2xpZGVzaG93IjoiNTYxNGEwZCJ9\" href='https:\/\/datascientest.com\/wp-content\/uploads\/2020\/12\/Lapprentissage-supervise\u0301-avec-scikit-learn-scaled.jpg'><img width=\"150\" height=\"150\" src=\"https:\/\/datascientest.com\/wp-content\/uploads\/2020\/12\/Lapprentissage-supervise\u0301-avec-scikit-learn-150x150.jpg\" class=\"attachment-thumbnail size-thumbnail\" alt=\"CheatSheet Apprentissage Supervis\u00e9\" decoding=\"async\" aria-describedby=\"gallery-1-68727\" srcset=\"https:\/\/datascientest.com\/wp-content\/uploads\/2020\/12\/Lapprentissage-supervise\u0301-avec-scikit-learn-150x150.jpg 150w, https:\/\/datascientest.com\/wp-content\/uploads\/2020\/12\/Lapprentissage-supervise\u0301-avec-scikit-learn-700x700.jpg 700w\" sizes=\"(max-width: 150px) 100vw, 150px\" \/><\/a>\n\t\t\t<\/div>\n\t\t\t\t<figcaption class='wp-caption-text gallery-caption' id='gallery-1-68727'>\n\t\t\t\tApprentissage supervis\u00e9\n\t\t\t\t<\/figcaption><\/figure><figure class='gallery-item'>\n\t\t\t<div class='gallery-icon portrait'>\n\t\t\t\t<a data-elementor-open-lightbox=\"yes\" data-elementor-lightbox-slideshow=\"5614a0d\" data-elementor-lightbox-title=\"CheatSheet Performance d&#039;un mod\u00e8le\" data-e-action-hash=\"#elementor-action%3Aaction%3Dlightbox%26settings%3DeyJpZCI6NzMzODAsInVybCI6Imh0dHBzOlwvXC9kYXRhc2NpZW50ZXN0LmNvbVwvd3AtY29udGVudFwvdXBsb2Fkc1wvMjAyMVwvMDZcL0NoZWF0U2hlZXQtU2Npa2l0LUxlYXJuLnBuZyIsInNsaWRlc2hvdyI6IjU2MTRhMGQifQ%3D%3D\" href='https:\/\/datascientest.com\/wp-content\/uploads\/2021\/06\/CheatSheet-Scikit-Learn.png'><img width=\"150\" height=\"150\" src=\"https:\/\/datascientest.com\/wp-content\/uploads\/2021\/06\/CheatSheet-Scikit-Learn-150x150.png\" class=\"attachment-thumbnail size-thumbnail\" alt=\"Performance d&#039;un mod\u00e8le\" decoding=\"async\" aria-describedby=\"gallery-1-73380\" \/><\/a>\n\t\t\t<\/div>\n\t\t\t\t<figcaption class='wp-caption-text gallery-caption' id='gallery-1-73380'>\n\t\t\t\tPerformance d&rsquo;un mod\u00e8le\n\t\t\t\t<\/figcaption><\/figure>\n\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-50a3d44 elementor-widget elementor-widget-html\" data-id=\"50a3d44\" 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\">\n{\n  \"@context\": \"https:\/\/schema.org\",\n  \"@type\": \"FAQPage\",\n  \"mainEntity\": [{\n    \"@type\": \"Question\",\n    \"name\": \"Qu\u2019est ce que Sckikit-Learn ?\",\n    \"acceptedAnswer\": {\n      \"@type\": \"Answer\",\n      \"text\": \"C\u2019est une librairie Python qui donne acc\u00e8s \u00e0 des versions efficaces d\u2019un grand nombre d\u2019algorithmes courants. Elle offre \u00e9galement une API propre et uniformis\u00e9e. Par cons\u00e9quent, un des gros avantages de Scikit-Learn est qu'une fois que vous avez compris l'utilisation et la syntaxe de base de Scikit-Learn pour un type de mod\u00e8le, le passage \u00e0 un nouveau mod\u00e8le ou algorithme est tr\u00e8s simple. La librairie ne permet pas seulement de faire de la mod\u00e9lisation, elle peut assurer \u00e9galement des \u00e9tapes de preprocessing ce que nous verrons dans la suite de l\u2019article.\"\n    }\n  },{\n    \"@type\": \"Question\",\n    \"name\": \"L\u2019API de Scikit-Learn\",\n    \"acceptedAnswer\": {\n      \"@type\": \"Answer\",\n      \"text\": \"Elle a \u00e9t\u00e9 construite selon certains principes de sorte \u00e0 la rendre tr\u00e8s facilement applicable \u00e0 un grand nombre de domaines\"\n    }\n  }]\n}\n<\/script>\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-d453ad5 elementor-widget elementor-widget-heading\" data-id=\"d453ad5\" 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\">L\u2019API de Scikit-Learn<\/h3>\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-85adc66 elementor-widget elementor-widget-text-editor\" data-id=\"85adc66\" 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>Elle a \u00e9t\u00e9 construite selon certains principes de sorte \u00e0 la rendre tr\u00e8s facilement applicable \u00e0 un grand nombre de domaines :<br \/>\u25cf <strong>Coh\u00e9rence :<\/strong> Tous les objets partagent une interface commune tir\u00e9e d&rsquo;un ensemble limit\u00e9 de m\u00e9thodes, avec une documentation coh\u00e9rente.<\/p><p>\u25cf <strong>Inspection :<\/strong> Toutes les valeurs des param\u00e8tres sp\u00e9cifi\u00e9s sont expos\u00e9es en tant qu&rsquo;attributs publics.<\/p><p>\u25cf <strong>Hi\u00e9rarchie d&rsquo;objets limit\u00e9e :<\/strong> Seuls les algorithmes sont repr\u00e9sent\u00e9s par des classes Python ; les ensembles de donn\u00e9es sont repr\u00e9sent\u00e9s dans des formats standard<br \/>(tableaux NumPy, DataFrames Pandas, matrices \u00e9parses SciPy) et les noms de param\u00e8tres utilisent des cha\u00eenes Python standard.<\/p><p>\u25cf <strong>Composition :<\/strong> De nombreuses t\u00e2ches d&rsquo;apprentissage automatique peuvent \u00eatre exprim\u00e9es comme des s\u00e9quences d&rsquo;algorithmes plus fondamentaux, et Scikit-Learn en fait usage chaque fois que cela est possible.<\/p><p>\u25cf <strong>Valeurs par d\u00e9faut raisonnables :<\/strong> Lorsque les mod\u00e8les n\u00e9cessitent des param\u00e8tres sp\u00e9cifi\u00e9s par l&rsquo;utilisateur, la biblioth\u00e8que d\u00e9finit une valeur par d\u00e9faut appropri\u00e9e. Ces principes sont directement d\u00e9crits dans ce papier pr\u00e9sentant les principes de l\u2019API de Scikit-Learn.<\/p><p>Ces 5 principes permettent dans la pratique une utilisation simple et fluide de la librairie m\u00eame pour des profils ne disposant pas d\u2019un bagage math\u00e9matique solide.<\/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-af17c78 elementor-widget elementor-widget-heading\" data-id=\"af17c78\" 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\">Les bases de Scikit-Learn<\/h3>\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-5332627 elementor-widget elementor-widget-text-editor\" data-id=\"5332627\" 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 l\u2019API est uniformis\u00e9e, Quel que soit le mod\u00e8le que vous envisagez d\u2019utiliser, les \u00e9tapes de mod\u00e9lisation sont souvent les m\u00eames : <\/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-3b73023 elementor-widget elementor-widget-image\" data-id=\"3b73023\" 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=\"800\" height=\"439\" src=\"https:\/\/datascientest.com\/wp-content\/uploads\/2021\/05\/illu_scikit_blog_2-09.png\" class=\"attachment-large size-large wp-image-73285\" alt=\"scikit learn\" srcset=\"https:\/\/datascientest.com\/wp-content\/uploads\/2021\/05\/illu_scikit_blog_2-09.png 1024w, https:\/\/datascientest.com\/wp-content\/uploads\/2021\/05\/illu_scikit_blog_2-09-300x165.png 300w, https:\/\/datascientest.com\/wp-content\/uploads\/2021\/05\/illu_scikit_blog_2-09-768x422.png 768w\" sizes=\"(max-width: 800px) 100vw, 800px\" \/>\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-e5ecd25 elementor-widget elementor-widget-text-editor\" data-id=\"e5ecd25\" 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<ul><li style=\"font-weight: 400;\" aria-level=\"1\"><strong>Choisir un mod\u00e8le <\/strong><span style=\"font-weight: 400;\">en important la classe appropri\u00e9e de Scikit-Learn.<br \/><\/span><\/li><li style=\"font-weight: 400;\" aria-level=\"1\"><b>Param\u00e9trer le mod\u00e8le<\/b><span style=\"font-weight: 400;\">. Si vous \u00eates d\u00e9j\u00e0 s\u00fbrs des param\u00e8tres que vous voulez utiliser vous pouvez les renseigner \u00e0 la main sinon la librairie offre aussi des techniques comme <\/span><i><span style=\"font-weight: 400;\">GridSeachCV<\/span><\/i><span style=\"font-weight: 400;\"> pour trouver les param\u00e8tres optimaux.\u00a0<\/span><\/li><li style=\"font-weight: 400;\" aria-level=\"1\"><b>Entra\u00eener le mod\u00e8le<\/b><span style=\"font-weight: 400;\"> sur le jeu d&rsquo;apprentissage\u00a0 \u00e0 l\u2019aide de la m\u00e9thode fit.\u00a0<\/span><\/li><li style=\"font-weight: 400;\" aria-level=\"1\"><b>Tester le mod\u00e8le<\/b><span style=\"font-weight: 400;\"> sur de nouvelles donn\u00e9es :\u00a0<\/span><ul><li style=\"font-weight: 400;\" aria-level=\"2\"><span style=\"font-weight: 400;\">Dans le cadre d\u2019<\/span><a href=\"https:\/\/datascientest.com\/apprentissage-supervise\">apprentissage supervis\u00e9<\/a><span style=\"font-weight: 400;\">, nous utilisons la m\u00e9thode <\/span><b>predict <\/b><span style=\"font-weight: 400;\">sur les donn\u00e9es test.\u00a0<\/span><\/li><li style=\"font-weight: 400;\" aria-level=\"2\"><span style=\"font-weight: 400;\">Dans le cadre d\u2019<\/span><a href=\"https:\/\/datascientest.com\/apprentissage-non-supervise\">apprentissage non supervis\u00e9<\/a><span style=\"font-weight: 400;\">, nous utilisons les m\u00e9thodes <\/span><b>transform <\/b><span style=\"font-weight: 400;\">ou <\/span><b>predict<\/b><span style=\"font-weight: 400;\">.\u00a0<\/span><\/li><\/ul><\/li><\/ul><p>Ces 4 \u00e9tapes sont en g\u00e9n\u00e9ral communes \u00e0 l\u2019utilisation d\u2019un grand nombre de mod\u00e8les disponibles dans la librairie ce qui permet, une fois que vous avez compris la logique de construction d\u2019un mod\u00e8le, de pouvoir tr\u00e8s facilement utiliser d\u2019autres mod\u00e8les.<\/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-7ed21c3 elementor-widget elementor-widget-heading\" data-id=\"7ed21c3\" 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\">Scikit-Learn : des possibilit\u00e9s nombreuses<\/h3>\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-4355a19 elementor-widget elementor-widget-image\" data-id=\"4355a19\" 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=\"800\" height=\"498\" src=\"https:\/\/datascientest.com\/wp-content\/uploads\/2021\/05\/ml_map-1024x638.png\" class=\"attachment-large size-large wp-image-66436\" alt=\"Cheat sheet scikit learn\" srcset=\"https:\/\/datascientest.com\/wp-content\/uploads\/2021\/05\/ml_map-1024x638.png 1024w, https:\/\/datascientest.com\/wp-content\/uploads\/2021\/05\/ml_map-300x187.png 300w, https:\/\/datascientest.com\/wp-content\/uploads\/2021\/05\/ml_map-768x479.png 768w, https:\/\/datascientest.com\/wp-content\/uploads\/2021\/05\/ml_map-1536x958.png 1536w, https:\/\/datascientest.com\/wp-content\/uploads\/2021\/05\/ml_map-2048x1277.png 2048w\" sizes=\"(max-width: 800px) 100vw, 800px\" \/>\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-9c0730f elementor-widget elementor-widget-text-editor\" data-id=\"9c0730f\" 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;\">Dans un <a href=\"https:\/\/datascientest.com\/5-etapes-pour-faire-un-test-statistique\">pr\u00e9c\u00e9dent article<\/a><\/span><span style=\"font-weight: 400;\">\u00a0nous vous avions parl\u00e9 des 5 \u00e9tapes cruciales d\u2019un projet data :<\/span><\/p><ul><li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">Saisir les tenants et aboutissants<\/span><\/li><li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">R\u00e9cup\u00e9rer et explorer les donn\u00e9es<\/span><\/li><li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">Pr\u00e9parer vos bases de travail<\/span><\/li><li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">S\u00e9lectionner et entra\u00eener un mod\u00e8le<\/span><\/li><li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">\u00c9valuer vos r\u00e9sultats<\/span><\/li><\/ul><p><span style=\"font-weight: 400;\">Dans les 3 derni\u00e8res \u00e9tapes <\/span><i><span style=\"font-weight: 400;\">Scikit-Learn <\/span><\/i><span style=\"font-weight: 400;\">est une librairie largement utilis\u00e9e qui vous fournit tous les outils n\u00e9cessaires :\u00a0<\/span><\/p><ul><li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">Pour <\/span><b>pr\u00e9parer vos donn\u00e9es<\/b><span style=\"font-weight: 400;\"> la librairie vous offre un arsenal de m\u00e9thodes que ce soit pour :<\/span><ul><li style=\"font-weight: 400;\" aria-level=\"2\"><b>S\u00e9parer vos donn\u00e9es<\/b><span style=\"font-weight: 400;\"> en jeu de test et d\u2019apprentissage \u00e0 l\u2019aide de fonction <\/span><i><span style=\"font-weight: 400;\">train_test_split. <\/span><\/i><span style=\"font-weight: 400;\">\u00a0<\/span><\/li><li style=\"font-weight: 400;\" aria-level=\"2\"><b>Encoder les variables<\/b> <b>qualitatives<\/b><span style=\"font-weight: 400;\"> avec des m\u00e9thodes comme <\/span><i><span style=\"font-weight: 400;\">OneHotEncoder.<\/span><\/i><\/li><li style=\"font-weight: 400;\" aria-level=\"2\"><b>Normaliser<\/b><span style=\"font-weight: 400;\"> les donn\u00e9es avant de les mod\u00e9liser avec des m\u00e9thodes comme <\/span><i><span style=\"font-weight: 400;\">StandardScaler <\/span><\/i><span style=\"font-weight: 400;\">par exemple.\u00a0<\/span><\/li><li style=\"font-weight: 400;\" aria-level=\"2\"><b>Traiter les valeurs manquantes<\/b><span style=\"font-weight: 400;\"> avec des m\u00e9thodes simples d\u2019imputation comme <\/span><i><span style=\"font-weight: 400;\">SimpleImputer <\/span><\/i><span style=\"font-weight: 400;\">ou bien plus avanc\u00e9es\u00a0 comme <\/span><i><span style=\"font-weight: 400;\">IterativeImputer<\/span><\/i><span style=\"font-weight: 400;\">.<\/span><\/li><li style=\"font-weight: 400;\" aria-level=\"2\"><span style=\"font-weight: 400;\">Faire de la <\/span><b>s\u00e9lection de variables<\/b><span style=\"font-weight: 400;\"> avec par exemple <\/span><i><span style=\"font-weight: 400;\">SelectKBest.\u00a0<\/span><\/i><\/li><li style=\"font-weight: 400;\" aria-level=\"2\"><b>R\u00e9duire la dimension<\/b><span style=\"font-weight: 400;\"> du jeu de donn\u00e9es \u00e0 l\u2019aide de m\u00e9thodes comme l\u2019ACP ou TSNE.<\/span><\/li><\/ul><\/li><\/ul><p><span style=\"font-weight: 400;\">Toutes ces m\u00e9thodes vous permettent de pr\u00e9parer les donn\u00e9es efficacement, \u00e9tape cruciale d\u2019un projet et <\/span><i><span style=\"font-weight: 400;\">Scikit-Learn <\/span><\/i><span style=\"font-weight: 400;\">vous offre tous les outils n\u00e9cessaires pour la r\u00e9ussir.<\/span><span style=\"font-weight: 400;\"> Nous avons cit\u00e9 en exemple une petite partie des m\u00e9thodes disponibles, <a href=\"https:\/\/scikit-learn.org\/stable\/index.html\">vous en trouverez bien d\u2019autres sur le site<\/a>.<\/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-264d727 elementor-align-center button-principale elementor-widget elementor-widget-button\" data-id=\"264d727\" 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=\"\/formations-data\">\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\">Se formation \u00e0 Scikit-Learn<\/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<div class=\"elementor-element elementor-element-d9c56db elementor-widget elementor-widget-spacer\" data-id=\"d9c56db\" data-element_type=\"widget\" data-widget_type=\"spacer.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-column .elementor-spacer-inner{height:var(--spacer-size)}.e-con{--container-widget-width:100%}.e-con-inner>.elementor-widget-spacer,.e-con>.elementor-widget-spacer{width:var(--container-widget-width,var(--spacer-size));--align-self:var(--container-widget-align-self,initial);--flex-shrink:0}.e-con-inner>.elementor-widget-spacer>.elementor-widget-container,.e-con-inner>.elementor-widget-spacer>.elementor-widget-container>.elementor-spacer,.e-con>.elementor-widget-spacer>.elementor-widget-container,.e-con>.elementor-widget-spacer>.elementor-widget-container>.elementor-spacer{height:100%}.e-con-inner>.elementor-widget-spacer>.elementor-widget-container>.elementor-spacer>.elementor-spacer-inner,.e-con>.elementor-widget-spacer>.elementor-widget-container>.elementor-spacer>.elementor-spacer-inner{height:var(--container-widget-height,var(--spacer-size))}<\/style>\t\t<div class=\"elementor-spacer\">\n\t\t\t<div class=\"elementor-spacer-inner\"><\/div>\n\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-3f69ea4 elementor-widget elementor-widget-heading\" data-id=\"3f69ea4\" 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\">Apprentissage supervis\u00e9 et non supervis\u00e9 sur Scikit-Learn <\/h3>\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-c0809e9 elementor-widget elementor-widget-text-editor\" data-id=\"c0809e9\" 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<ul><li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">Pour s\u00e9lectionner et entra\u00eener un mod\u00e8le, <\/span><i><span style=\"font-weight: 400;\">Scikit-Learn <\/span><\/i><span style=\"font-weight: 400;\">couvre deux grands types d\u2019apprentissage :\u00a0<\/span><ul><li style=\"font-weight: 400;\" aria-level=\"2\"><a href=\"https:\/\/datascientest.com\/apprentissage-supervise\">L\u2019apprentissage supervis\u00e9<\/a><span style=\"font-weight: 400;\"> : de nombreux mod\u00e8les comme la <\/span><b>r\u00e9gression <\/b><span style=\"font-weight: 400;\">logistique, la r\u00e9gression lin\u00e9aire, les r\u00e9gressions lin\u00e9aires p\u00e9nalis\u00e9es comme Ridge, Lasso ou elastic net, les <\/span><a href=\"https:\/\/datascientest.com\/random-forest-definition\">arbres de d\u00e9cisions<\/a><span style=\"font-weight: 400;\">, les m\u00e9thodes d\u2019ensemble comme les <\/span><b>for\u00eats al\u00e9atoires<\/b><span style=\"font-weight: 400;\"> ou bien encore les m\u00e9thodes de <\/span><b>boosting<\/b><span style=\"font-weight: 400;\"> sont disponibles et facilement utilisables pour traiter aussi bien des probl\u00e9matiques de classification et de r\u00e9gression.<\/span><\/li><li style=\"font-weight: 400;\" aria-level=\"2\"><a href=\"https:\/\/datascientest.com\/apprentissage-non-supervise\">L\u2019apprentissage non supervis\u00e9<\/a><span style=\"font-weight: 400;\"> : L\u00e0 encore l\u2019algorithme des <\/span><b>k-moyennes<\/b><span style=\"font-weight: 400;\">, la <\/span><b>classification ascendante hi\u00e9rarchique<\/b><span style=\"font-weight: 400;\">, <\/span><b>DBSCAN<\/b><span style=\"font-weight: 400;\">, les m\u00e9langes gaussiens sont autant de mod\u00e8les disponibles et facilement utilisables.\u00a0<\/span><\/li><\/ul><\/li><\/ul><p><span style=\"font-weight: 400;\">Pour la plupart de ces mod\u00e8les, surtout en apprentissage supervis\u00e9, nous ne connaissons pas \u00e0 l\u2019avance les meilleurs param\u00e8tres \u00e0 utiliser pour obtenir la meilleure performance possible. Ainsi <\/span><i><span style=\"font-weight: 400;\">Scikit-Learn <\/span><\/i><span style=\"font-weight: 400;\">offre des outils comme GridSearchCV ou RandomizedSearchCV qui permettent par <\/span><b>validation crois\u00e9e<\/b><span style=\"font-weight: 400;\"> de d\u00e9terminer les meilleurs param\u00e8tres de notre mod\u00e8le. Ces deux fonctions sont tr\u00e8s largement utilis\u00e9es par la communaut\u00e9 au moment de mod\u00e9liser les donn\u00e9es.\u00a0<\/span><\/p><p><span style=\"font-weight: 400;\">La grande vari\u00e9t\u00e9 de mod\u00e8les propos\u00e9s dans une seule librairie fait de <\/span><i><span style=\"font-weight: 400;\">Scikit-Learn <\/span><\/i><span style=\"font-weight: 400;\">un incontournable de l&rsquo;\u00e9tape de mod\u00e9lisation des donn\u00e9es dans un projet data.\u00a0<\/span><\/p><p><span style=\"font-weight: 400;\">Pour <\/span><b>\u00e9valuer vos r\u00e9sultats<\/b><span style=\"font-weight: 400;\">, <\/span><i><span style=\"font-weight: 400;\">Scikit-Learn <\/span><\/i><span style=\"font-weight: 400;\">se r\u00e9v\u00e8le encore redoutable. Ce ne sont pas moins de <\/span><b>40 m\u00e9triques disponibles<\/b><span style=\"font-weight: 400;\"> et pr\u00eates \u00e0 l\u2019emploi pour \u00e9valuer les r\u00e9sultats de vos mod\u00e8les. Certaines comme la <\/span><i><span style=\"font-weight: 400;\">RMSE, MAE, MSE, r2_score <\/span><\/i><span style=\"font-weight: 400;\">permettent d\u2019\u00e9valuer et de comparer les r\u00e9sultats de mod\u00e8les de r\u00e9gression. D\u2019autres comme <\/span><i><span style=\"font-weight: 400;\">confusion_matrix<\/span><\/i><span style=\"font-weight: 400;\">, <\/span><i><span style=\"font-weight: 400;\">accuracy_score, classification_report<\/span><\/i><span style=\"font-weight: 400;\"> permettent d\u2019\u00e9valuer et de comparer les r\u00e9sultats de mod\u00e8les de classification. Enfin il en existe aussi comme la <\/span><i><span style=\"font-weight: 400;\">silhouette_score <\/span><\/i><span style=\"font-weight: 400;\">pour \u00e9valuer la performance d\u2019algorithmes de partitionnement comme la classification ascendante hi\u00e9rarchique.<\/span><\/p><p><span style=\"font-weight: 400;\">Il est important d\u2019ajouter aussi que <\/span><i><span style=\"font-weight: 400;\">Scikit-Learn <\/span><\/i><span style=\"font-weight: 400;\">gr\u00e2ce \u00e0 une m\u00e9thode nomm\u00e9e <\/span><b><i>pipeline <\/i><\/b><span style=\"font-weight: 400;\">permet d\u2019<\/span><b>instancier les 3 derni\u00e8res \u00e9tapes<\/b><span style=\"font-weight: 400;\"> d\u2019un projet en tr\u00e8s peu de lignes de code. Bien s\u00fbr, cet outil s\u2019utilise apr\u00e8s avoir test\u00e9 diff\u00e9rents mod\u00e8les et d\u00e9terminer le meilleur pour notre probl\u00e8me. <\/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-4132f87 elementor-align-center button-principale elementor-widget elementor-widget-button\" data-id=\"4132f87\" 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=\"\/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\">Apprenez \u00e0 utiliser Scikit-Learn<\/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<div class=\"elementor-element elementor-element-9f531fb elementor-widget elementor-widget-heading\" data-id=\"9f531fb\" 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\">Un peu de pratique<\/h3>\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-ec7e044 elementor-widget elementor-widget-text-editor\" data-id=\"ec7e044\" 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;\">Regardons un exemple concret pour comprendre la capacit\u00e9 de <\/span><i><span style=\"font-weight: 400;\">Scikit-Learn<\/span><\/i><span style=\"font-weight: 400;\"> \u00e0 nous offrir des outils statistiques pour mener \u00e0 bien un projet data avec un minimum de lignes de code.\u00a0<\/span><\/p><p><span style=\"font-weight: 400;\">Dans cet exemple, nous allons utiliser le jeu de donn\u00e9es <\/span><b>boston house-prices<\/b><span style=\"font-weight: 400;\"> mis \u00e0 disposition par la librairie et nous allons travailler dessus. Ce dernier ne contient pas de valeurs manquantes et notre objectif sera de <\/span><b>tester 3 mod\u00e8les diff\u00e9rents<\/b><span style=\"font-weight: 400;\">, de trouver pour chacun les param\u00e8tres optimaux puis de comparer les scores obtenus pour d\u00e9terminer le meilleur.<\/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-38c1473 elementor-widget elementor-widget-shortcode\" data-id=\"38c1473\" data-element_type=\"widget\" data-widget_type=\"shortcode.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<div class=\"elementor-shortcode\"><script src=\"https:\/\/gist.github.com\/Thibault-venet\/8d9c974464561a530f472d4e159ed27d.js\"><\/script><\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-8ee8e20 elementor-widget elementor-widget-text-editor\" data-id=\"8ee8e20\" 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;\">Gist code exemple :\u00a0<\/span><\/p><p><span style=\"font-weight: 400;\">Le code peut se d\u00e9couper en 4 \u00e9tapes :\u00a0<\/span><\/p><ul><li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">Import et scaling des donn\u00e9es \u00e0 l\u2019aide de la classe <\/span><i><span style=\"font-weight: 400;\">StandardScaler.<\/span><\/i><\/li><li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">S\u00e9lection de variables en utilisant la classe <\/span><i><span style=\"font-weight: 400;\">SelectKBest<\/span><\/i><span style=\"font-weight: 400;\">.<\/span><\/li><li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">Entra\u00eenement de 3 mod\u00e8les diff\u00e9rents et recherche des meilleurs param\u00e8tres \u00e0 l\u2019aide de la classe <\/span><i><span style=\"font-weight: 400;\">GridSearchCV.<\/span><\/i><\/li><li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">Comparaison et choix du mod\u00e8le optimal.\u00a0<\/span><\/li><\/ul><p><span style=\"font-weight: 400;\">Une derni\u00e8re \u00e9tape consiste \u00e0 <\/span><b>instancier toutes ses \u00e9tapes en une seule ligne de code <\/b><span style=\"font-weight: 400;\">avec le meilleur mod\u00e8le en utilisant la classe <\/span><i><span style=\"font-weight: 400;\">pipeline<\/span><\/i><span style=\"font-weight: 400;\"> et pr\u00e9dire et \u00e9valuer sur le jeu de test.\u00a0<\/span><\/p>\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t<section class=\"elementor-section elementor-top-section elementor-element elementor-element-47c94d9 elementor-section-boxed elementor-section-height-default elementor-section-height-default\" data-id=\"47c94d9\" data-element_type=\"section\">\n\t\t\t\t\t\t<div class=\"elementor-container elementor-column-gap-default\">\n\t\t\t\t\t<div class=\"elementor-column elementor-col-100 elementor-top-column elementor-element elementor-element-99bf2f9\" data-id=\"99bf2f9\" data-element_type=\"column\">\n\t\t\t<div class=\"elementor-widget-wrap elementor-element-populated\">\n\t\t\t\t\t\t\t\t<div class=\"elementor-element elementor-element-f034270 elementor-widget elementor-widget-shortcode\" data-id=\"f034270\" data-element_type=\"widget\" data-widget_type=\"shortcode.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<div class=\"elementor-shortcode\"><script src=\"https:\/\/gist.github.com\/Thibault-venet\/c0cce5f66cde7b43e025349f5e13bd4b.js\"><\/script><\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t<section class=\"elementor-section elementor-top-section elementor-element elementor-element-0ea04a2 elementor-section-boxed elementor-section-height-default elementor-section-height-default\" data-id=\"0ea04a2\" data-element_type=\"section\">\n\t\t\t\t\t\t<div class=\"elementor-container elementor-column-gap-default\">\n\t\t\t\t\t<div class=\"elementor-column elementor-col-100 elementor-top-column elementor-element elementor-element-71d46af\" data-id=\"71d46af\" data-element_type=\"column\">\n\t\t\t<div class=\"elementor-widget-wrap elementor-element-populated\">\n\t\t\t\t\t\t\t\t<div class=\"elementor-element elementor-element-c7cba22 elementor-widget elementor-widget-text-editor\" data-id=\"c7cba22\" 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 librairie <\/span><i><span style=\"font-weight: 400;\">Scikit-Learn <\/span><\/i><span style=\"font-weight: 400;\">aujourd\u2019hui fournit un tr\u00e8s grand nombre d\u2019algorithmes avec des champs d\u2019application dans de nombreux secteurs comme l\u2019industrie, l\u2019assurance, la compr\u00e9hension des donn\u00e9es clients\u2026 Chez Datascientest nous vous apprendrons \u00e0 utiliser, comprendre, interpr\u00e9ter et \u00e9valuer un grand nombre d\u2019algorithmes de la librairie sur des probl\u00e9matiques concr\u00e8tes. N\u2019h\u00e9sitez pas \u00e0 d\u00e9couvrir nos formations.<\/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-a395d62 elementor-align-center button-principale elementor-widget elementor-widget-button\" data-id=\"a395d62\" 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\/formations-data\">\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\u00e9couvrez nos formations en Data Science<\/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<\/div>\n\t\t\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t\t\t\t<\/div>\n\t\t","protected":false},"excerpt":{"rendered":"<p>Si vous \u00e9tudiez des donn\u00e9es et que vous souhaitez en tirer de l\u2019information, vous devrez souvent traiter les donn\u00e9es, les modifier et surtout construire des mod\u00e8les capables d\u2019apprendre des sch\u00e9mas dans vos donn\u00e9es pour une probl\u00e9matique choisie. Beaucoup de librairies open source permettent aujourd\u2019hui de le faire, mais la plus connue d\u2019entre elles est s\u00fbrement [&hellip;]<\/p>\n","protected":false},"author":77,"featured_media":73293,"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>Scikit-Learn : D\u00e9couvrez la librairie Python d\u00e9di\u00e9 au Machine Learning<\/title>\n<meta name=\"description\" content=\"Si vous \u00e9tudiez des donn\u00e9es et que vous souhaitez en tirer de l\u2019information, vous devrez souvent traiter les donn\u00e9es, les modifier et surtout construire des mod\u00e8les capables d\u2019apprendre des sch\u00e9mas dans vos donn\u00e9es pour une probl\u00e9matique choisie. 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