{"id":5859,"date":"2023-09-08T14:22:38","date_gmt":"2023-09-08T12:22:38","guid":{"rendered":"https:\/\/francestat.com\/?page_id=5859"},"modified":"2024-12-02T17:22:00","modified_gmt":"2024-12-02T16:22:00","slug":"uniwin-apriori","status":"publish","type":"page","link":"https:\/\/francestat.com\/index.php\/uniwin-apriori\/","title":{"rendered":"Uniwin – APRIORI"},"content":{"rendered":"

[vc_row][vc_column]

<\/div>

UNIWIN - Analyse APRIORI<\/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]L’algorithme APRIORI est un algorithme d’exploration de donn\u00e9es con\u00e7u en 1994 par Rakesh Agrawal et Ramakrishnan Sikrant dans le domaine de l’apprentissage des r\u00e8gles d’association. Il sert \u00e0 reconna\u00eetre des propri\u00e9t\u00e9s qui reviennent fr\u00e9quemment dans un ensemble de donn\u00e9es et \u00e0 d\u00e9tecter les relations ou les associations entre des modalit\u00e9s sp\u00e9cifiques de variables cat\u00e9gorielles dans des fichiers de donn\u00e9es volumineux.<\/p>\n

Cette technique exploratoire puissante poss\u00e8de toute une gamme d’applications dans de nombreux domaines : analyse des tickets de caisse, campagne marketing, analyse de log Web, d\u00e9tection de fraudeurs, analyse de d\u00e9faillances de process.<\/p>\n

Cette proc\u00e9dure est bas\u00e9e sur le package R ‘arules’.[\/vc_column_text][\/vc_column][\/vc_row][vc_row][vc_column][vc_single_image image=\u00a0\u00bb6408″ 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

Tableaux<\/u><\/span><\/strong><\/p>\n\n\n<\/colgroup>\n\n\n\n\n\n\n\n\n\n
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Libell\u00e9s des colonnes<\/p>\n<\/td>\n<\/tr>\n

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Libell\u00e9s des modalit\u00e9s des colonnes<\/p>\n<\/td>\n<\/tr>\n

\n

Motifs fr\u00e9quents<\/p>\n<\/td>\n<\/tr>\n

\n

Motifs fr\u00e9quents ferm\u00e9s<\/p>\n<\/td>\n<\/tr>\n

\n

Motifs fr\u00e9quents maximaux<\/p>\n<\/td>\n<\/tr>\n

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D\u00e9tails des r\u00e8gles<\/p>\n<\/td>\n<\/tr>\n

\n

R\u00e8gles pour la colonne cible<\/p>\n<\/td>\n<\/tr>\n

\n

Occurrences et fr\u00e9quences des modalit\u00e9s de la colonne cible<\/p>\n<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n

Graphiques<\/u><\/span><\/strong><\/p>\n\n\n<\/colgroup>\n\n\n\n\n\n\n\n\n
\n

Graphique du lift vs cons\u00e9quent x ant\u00e9c\u00e9dent<\/p>\n<\/td>\n<\/tr>\n

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Graphique de la confiance vs cons\u00e9quent x ant\u00e9c\u00e9dent<\/p>\n<\/td>\n<\/tr>\n

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Graphique du support vs cons\u00e9quent x ant\u00e9c\u00e9dent<\/p>\n<\/td>\n<\/tr>\n

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Graphique du lift par rapport au support<\/p>\n<\/td>\n<\/tr>\n

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Graphique du lift par rapport \u00e0 la confiance<\/p>\n<\/td>\n<\/tr>\n

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Graphique du lift par rapport au support pour la colonne cible<\/p>\n<\/td>\n<\/tr>\n

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Graphique du lift par rapport \u00e0 la confiance pour la colonne cible<\/p>\n<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n

[\/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%2FAnalyse%2520APRIORI.pdf|title:UNIWIN%20-%20APRIORI\u00a0\u00bb][\/vc_column][\/vc_row]<\/p>\n","protected":false},"excerpt":{"rendered":"

[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]L’algorithme APRIORI est un algorithme d’exploration de donn\u00e9es con\u00e7u en 1994 par Rakesh Agrawal et Ramakrishnan Sikrant dans le domaine de l’apprentissage des r\u00e8gles d’association. Il sert \u00e0 reconna\u00eetre des propri\u00e9t\u00e9s qui reviennent fr\u00e9quemment dans un ensemble de donn\u00e9es et \u00e0 d\u00e9tecter les relations ou les associations entre des modalit\u00e9s sp\u00e9cifiques de variables cat\u00e9gorielles dans…<\/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-5859","page","type-page","status-publish","hentry","description-off"],"yoast_head":"\nUniwin - APRIORI - FRANCESTAT<\/title>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/francestat.com\/index.php\/uniwin-apriori\/\" \/>\n<meta property=\"og:locale\" content=\"fr_FR\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Uniwin - APRIORI - FRANCESTAT\" \/>\n<meta property=\"og:description\" content=\"[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]L’algorithme APRIORI est un algorithme d’exploration de donn\u00e9es con\u00e7u en 1994 par Rakesh Agrawal et Ramakrishnan Sikrant dans le domaine de l’apprentissage des r\u00e8gles d’association. Il sert \u00e0 reconna\u00eetre des propri\u00e9t\u00e9s qui reviennent fr\u00e9quemment dans un ensemble de donn\u00e9es et \u00e0 d\u00e9tecter les relations ou les associations entre des modalit\u00e9s sp\u00e9cifiques de variables cat\u00e9gorielles dans…\" \/>\n<meta property=\"og:url\" content=\"https:\/\/francestat.com\/index.php\/uniwin-apriori\/\" \/>\n<meta property=\"og:site_name\" content=\"FRANCESTAT\" \/>\n<meta property=\"article:modified_time\" content=\"2024-12-02T16:22:00+00:00\" \/>\n<meta name=\"twitter:card\" content=\"summary_large_image\" \/>\n<meta name=\"twitter:label1\" content=\"Dur\u00e9e de lecture estim\u00e9e\" \/>\n\t<meta name=\"twitter:data1\" content=\"2 minutes\" \/>\n<script type=\"application\/ld+json\" class=\"yoast-schema-graph\">{\"@context\":\"https:\\\/\\\/schema.org\",\"@graph\":[{\"@type\":\"WebPage\",\"@id\":\"https:\\\/\\\/francestat.com\\\/index.php\\\/uniwin-apriori\\\/\",\"url\":\"https:\\\/\\\/francestat.com\\\/index.php\\\/uniwin-apriori\\\/\",\"name\":\"Uniwin - APRIORI - FRANCESTAT\",\"isPartOf\":{\"@id\":\"https:\\\/\\\/francestat.com\\\/#website\"},\"datePublished\":\"2023-09-08T12:22:38+00:00\",\"dateModified\":\"2024-12-02T16:22:00+00:00\",\"breadcrumb\":{\"@id\":\"https:\\\/\\\/francestat.com\\\/index.php\\\/uniwin-apriori\\\/#breadcrumb\"},\"inLanguage\":\"fr-FR\",\"potentialAction\":[{\"@type\":\"ReadAction\",\"target\":[\"https:\\\/\\\/francestat.com\\\/index.php\\\/uniwin-apriori\\\/\"]}]},{\"@type\":\"BreadcrumbList\",\"@id\":\"https:\\\/\\\/francestat.com\\\/index.php\\\/uniwin-apriori\\\/#breadcrumb\",\"itemListElement\":[{\"@type\":\"ListItem\",\"position\":1,\"name\":\"Accueil\",\"item\":\"https:\\\/\\\/francestat.com\\\/\"},{\"@type\":\"ListItem\",\"position\":2,\"name\":\"Uniwin – APRIORI\"}]},{\"@type\":\"WebSite\",\"@id\":\"https:\\\/\\\/francestat.com\\\/#website\",\"url\":\"https:\\\/\\\/francestat.com\\\/\",\"name\":\"FRANCESTAT\",\"description\":\"Logiciels, formations et services statistiques\",\"publisher\":{\"@id\":\"https:\\\/\\\/francestat.com\\\/#organization\"},\"potentialAction\":[{\"@type\":\"SearchAction\",\"target\":{\"@type\":\"EntryPoint\",\"urlTemplate\":\"https:\\\/\\\/francestat.com\\\/?s={search_term_string}\"},\"query-input\":{\"@type\":\"PropertyValueSpecification\",\"valueRequired\":true,\"valueName\":\"search_term_string\"}}],\"inLanguage\":\"fr-FR\"},{\"@type\":\"Organization\",\"@id\":\"https:\\\/\\\/francestat.com\\\/#organization\",\"name\":\"FRANCESTAT\",\"url\":\"https:\\\/\\\/francestat.com\\\/\",\"logo\":{\"@type\":\"ImageObject\",\"inLanguage\":\"fr-FR\",\"@id\":\"https:\\\/\\\/francestat.com\\\/#\\\/schema\\\/logo\\\/image\\\/\",\"url\":\"https:\\\/\\\/francestat.com\\\/wp-content\\\/uploads\\\/2018\\\/05\\\/logo_horizontal_small_francestat.jpg\",\"contentUrl\":\"https:\\\/\\\/francestat.com\\\/wp-content\\\/uploads\\\/2018\\\/05\\\/logo_horizontal_small_francestat.jpg\",\"width\":155,\"height\":51,\"caption\":\"FRANCESTAT\"},\"image\":{\"@id\":\"https:\\\/\\\/francestat.com\\\/#\\\/schema\\\/logo\\\/image\\\/\"}}]}<\/script>\n<!-- \/ Yoast SEO plugin. -->","yoast_head_json":{"title":"Uniwin - APRIORI - 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-apriori\/","og_locale":"fr_FR","og_type":"article","og_title":"Uniwin - APRIORI - 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]L’algorithme APRIORI est un algorithme d’exploration de donn\u00e9es con\u00e7u en 1994 par Rakesh Agrawal et Ramakrishnan Sikrant dans le domaine de l’apprentissage des r\u00e8gles d’association. 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