{"id":5804,"date":"2023-09-04T10:59:45","date_gmt":"2023-09-04T08:59:45","guid":{"rendered":"https:\/\/francestat.com\/?page_id=5804"},"modified":"2024-07-11T11:27:25","modified_gmt":"2024-07-11T09:27:25","slug":"uniwin-som","status":"publish","type":"page","link":"https:\/\/francestat.com\/index.php\/uniwin-som\/","title":{"rendered":"Uniwin &#8211; SOM"},"content":{"rendered":"<p>[vc_row][vc_column]<div id=\"ultimate-heading-84336a0390264623a\" class=\"uvc-heading ult-adjust-bottom-margin ultimate-heading-84336a0390264623a uvc-7395  uvc-heading-default-font-sizes\" data-hspacer=\"no_spacer\"  data-halign=\"center\" style=\"text-align:center\"><div class=\"uvc-heading-spacer no_spacer\" style=\"top\"><\/div><div class=\"uvc-main-heading ult-responsive\"  data-ultimate-target='.uvc-heading.ultimate-heading-84336a0390264623a h2'  data-responsive-json-new='{\"font-size\":\"\",\"line-height\":\"\"}' ><h2 style=\"--font-weight:theme;\">UNIWIN - Classification par cartes auto-organisatrices<\/h2><\/div><\/div>[\/vc_column][\/vc_row][vc_row][vc_column][vc_empty_space][\/vc_column][\/vc_row][vc_row][vc_column][vc_column_text]Les cartes auto-adaptatives, cartes auto-organisatrices ou cartes topologiques forment une classe de r\u00e9seau de neurones artificiels fond\u00e9e sur des m\u00e9thodes d&rsquo;apprentissage non-supervis\u00e9es.\u00a0Elles sont souvent d\u00e9sign\u00e9es par le terme anglais \u00ab self organizing maps \u00bb (SOM), ou encore cartes de Kohonen du nom du statisticien ayant d\u00e9velopp\u00e9 le concept en 1984.\u00a0La litt\u00e9rature utilise aussi les d\u00e9nominations : \u00ab r\u00e9seau de Kohonen \u00bb, \u00ab r\u00e9seau auto-adaptatif \u00bb ou \u00ab r\u00e9seau auto-organis\u00e9 \u00bb.<\/p>\n<p>Elles sont utilis\u00e9es pour cartographier un espace r\u00e9el, c&rsquo;est-\u00e0-dire pour \u00e9tudier la r\u00e9partition de donn\u00e9es dans un espace \u00e0 grande dimension. En pratique, cette cartographie peut servir \u00e0 r\u00e9aliser des t\u00e2ches de discr\u00e9tisation, quantification vectorielle ou classification (source Wikip\u00e9dia).<\/p>\n<p>Cette proc\u00e9dure est bas\u00e9e sur le package R &lsquo;kohonen&rsquo;.[\/vc_column_text][\/vc_column][\/vc_row][vc_row][vc_column][vc_single_image image=\u00a0\u00bb6390&Prime; img_size=\u00a0\u00bblarge\u00a0\u00bb alignment=\u00a0\u00bbcenter\u00a0\u00bb][\/vc_column][\/vc_row][vc_row][vc_column][vc_empty_space height=\u00a0\u00bb5px\u00a0\u00bb][\/vc_column][\/vc_row][vc_row][vc_column][vc_column_text]<\/p>\n<p class=\"hcp4\"><strong><span style=\"font-size: 10pt; font-family: Verdana, sans-serif;\"><u>Tableaux<\/u><\/span><\/strong><\/p>\n<table class=\"hcp3\" width=\"100%\" cellspacing=\"0\" bgcolor=\"#ffffff\">\n<colgroup>\n<col \/><\/colgroup>\n<tbody>\n<tr>\n<td>\n<p class=\"hcp1\" style=\"font-size: 10pt; font-family: Verdana, sans-serif;\">Effectifs dans les noeuds<\/p>\n<\/td>\n<\/tr>\n<tr>\n<td>\n<p class=\"hcp1\" style=\"font-size: 10pt; font-family: Verdana, sans-serif;\">Affectations des noeuds<\/p>\n<\/td>\n<\/tr>\n<tr>\n<td>\n<p class=\"hcp1\" style=\"font-size: 10pt; font-family: Verdana, sans-serif;\">Affectations des observations<\/p>\n<\/td>\n<\/tr>\n<tr>\n<td>\n<p class=\"hcp1\" style=\"font-size: 10pt; font-family: Verdana, sans-serif;\">Profils des noeuds<\/p>\n<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<p class=\"hcp4\"><strong><span style=\"font-size: 10pt; font-family: Verdana, sans-serif;\"><u>Graphiques<\/u><\/span><\/strong><\/p>\n<table class=\"hcp3\" width=\"100%\" cellspacing=\"0\" bgcolor=\"#ffffff\">\n<colgroup>\n<col \/><\/colgroup>\n<tbody>\n<tr>\n<td>\n<p class=\"hcp1\" style=\"font-size: 10pt; font-family: Verdana, sans-serif;\">Graphique de la progression de l&rsquo;apprentissage<\/p>\n<\/td>\n<\/tr>\n<tr>\n<td>\n<p class=\"hcp1\" style=\"font-size: 10pt; font-family: Verdana, sans-serif;\">Graphique des effectifs dans les noeuds<\/p>\n<\/td>\n<\/tr>\n<tr>\n<td>\n<p class=\"hcp1\" style=\"font-size: 10pt; font-family: Verdana, sans-serif;\">Graphique des observations dans les noeuds<\/p>\n<\/td>\n<\/tr>\n<tr>\n<td>\n<p class=\"hcp1\" style=\"font-size: 10pt; font-family: Verdana, sans-serif;\">Graphique des distances entre les noeuds<\/p>\n<\/td>\n<\/tr>\n<tr>\n<td>\n<p class=\"hcp1\" style=\"font-size: 10pt; font-family: Verdana, sans-serif;\">Graphique de la qualit\u00e9 des noeuds<\/p>\n<\/td>\n<\/tr>\n<tr>\n<td>\n<p class=\"hcp1\" style=\"font-size: 10pt; font-family: Verdana, sans-serif;\">Graphique des profils des noeuds<\/p>\n<\/td>\n<\/tr>\n<tr>\n<td>\n<p class=\"hcp1\" style=\"font-size: 10pt; font-family: Verdana, sans-serif;\">Carte thermique individuelle<\/p>\n<\/td>\n<\/tr>\n<tr>\n<td>\n<p class=\"hcp1\" style=\"font-size: 10pt; font-family: Verdana, sans-serif;\">Ensemble des cartes thermiques<\/p>\n<\/td>\n<\/tr>\n<tr>\n<td>\n<p class=\"hcp1\" style=\"font-size: 10pt; font-family: Verdana, sans-serif;\">Classification ascendante hi\u00e9rarchique<\/p>\n<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<p>[\/vc_column_text][\/vc_column][\/vc_row][vc_row][vc_column][vc_empty_space height=\u00a0\u00bb5px\u00a0\u00bb][\/vc_column][\/vc_row][vc_row][vc_column][vc_btn title=\u00a0\u00bbConsulter la documentation compl\u00e8te\u00a0\u00bb align=\u00a0\u00bbcenter\u00a0\u00bb link=\u00a0\u00bburl:https%3A%2F%2Ffrancestat.com%2Ftelecharg%2FUniwin%2Fpdf%2FClassification%2520par%2520cartes%2520auto-organisatrices.pdf|title:UNIWIN%20-%20SOM\u00a0\u00bb][\/vc_column][\/vc_row]<\/p>\n","protected":false},"excerpt":{"rendered":"<p>[vc_row][vc_column][\/vc_column][\/vc_row][vc_row][vc_column][vc_empty_space][\/vc_column][\/vc_row][vc_row][vc_column][vc_column_text]Les cartes auto-adaptatives, cartes auto-organisatrices ou cartes topologiques forment une classe de r\u00e9seau de neurones artificiels fond\u00e9e sur des m\u00e9thodes d&rsquo;apprentissage non-supervis\u00e9es.\u00a0Elles sont souvent d\u00e9sign\u00e9es par le terme anglais \u00ab self organizing maps \u00bb (SOM), ou encore cartes de Kohonen du nom du statisticien ayant d\u00e9velopp\u00e9 le concept en 1984.\u00a0La litt\u00e9rature utilise aussi les d\u00e9nominations&hellip;<\/p>\n","protected":false},"author":1,"featured_media":0,"parent":0,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"","meta":{"footnotes":""},"class_list":["post-5804","page","type-page","status-publish","hentry","description-off"],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v27.6 - 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SOM - FRANCESTAT","robots":{"index":"index","follow":"follow","max-snippet":"max-snippet:-1","max-image-preview":"max-image-preview:large","max-video-preview":"max-video-preview:-1"},"canonical":"https:\/\/francestat.com\/index.php\/uniwin-som\/","og_locale":"fr_FR","og_type":"article","og_title":"Uniwin - SOM - FRANCESTAT","og_description":"[vc_row][vc_column][\/vc_column][\/vc_row][vc_row][vc_column][vc_empty_space][\/vc_column][\/vc_row][vc_row][vc_column][vc_column_text]Les cartes auto-adaptatives, cartes auto-organisatrices ou cartes topologiques forment une classe de r\u00e9seau de neurones artificiels fond\u00e9e sur des m\u00e9thodes d&rsquo;apprentissage non-supervis\u00e9es.\u00a0Elles sont souvent d\u00e9sign\u00e9es par le terme anglais \u00ab self organizing maps \u00bb (SOM), ou encore cartes de Kohonen du nom du statisticien ayant d\u00e9velopp\u00e9 le concept en 1984.\u00a0La litt\u00e9rature utilise aussi les d\u00e9nominations&hellip;","og_url":"https:\/\/francestat.com\/index.php\/uniwin-som\/","og_site_name":"FRANCESTAT","article_modified_time":"2024-07-11T09:27:25+00:00","twitter_card":"summary_large_image","twitter_misc":{"Dur\u00e9e de lecture estim\u00e9e":"1 minute"},"schema":{"@context":"https:\/\/schema.org","@graph":[{"@type":"WebPage","@id":"https:\/\/francestat.com\/index.php\/uniwin-som\/","url":"https:\/\/francestat.com\/index.php\/uniwin-som\/","name":"Uniwin - 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