{"id":3210,"date":"2015-08-06T10:42:08","date_gmt":"2015-08-06T09:42:08","guid":{"rendered":"https:\/\/abcdr.guyader.pro\/?p=3210"},"modified":"2018-04-08T00:02:27","modified_gmt":"2018-04-07T23:02:27","slug":"comment-faire-une-analyse-en-composantes-principale-acp-sur-r-pca-plot-pca","status":"publish","type":"post","link":"https:\/\/thinkr.fr\/abcdr\/comment-faire-une-analyse-en-composantes-principale-acp-sur-r-pca-plot-pca\/","title":{"rendered":"Comment faire une Analyse en Composantes Principale (ACP) sur R ? PCA, plot.PCA"},"content":{"rendered":"<p>La fonction <b>PCA()<\/b> permet d\u2019effectuer une ACP.<\/p>\n<pre><code><br \/>library(FactoMineR)\n\nres_pca &lt;- PCA (iris, quali.sup=5)\n\n#On r\u00e9alise une ACP sur les 4 variables quantitatives du jeu de donn\u00e9es iris\n\n#La 5<sup>\u00e8me<\/sup> variable qui correspond au nom de la vari\u00e9t\u00e9 est qualitative\n\n#Nous pla\u00e7ons cette variable en suppl\u00e9mentaire,\n\n#cette variable ne participera donc pas \u00e0 la construction de l\u2019ACP,\n\n#mais elle apportera de l\u2019information suppl\u00e9mentaire\n\n\u00a0\n\nplot.PCA(res_pca,col.quali=\"blue\", label=\"quali\")\n\n#La fonction plot.PCA contient de nombreux param\u00e8tres modulables\n\n#ici nous choisissons la couleur de la variable qualitative\n\n#et de cacher l\u2019\u00e9tiquette des individus gr\u00e2ce au param\u00e8tre \u00ab\u00a0label\u00a0\u00bb\n\n<\/code><\/pre>\n<p>\u00a0<\/p>\n<p>Pour pouvoir d\u00e9crire les r\u00e9sultats de cette analyse nous avons besoin d\u2019\u00e9tudier les coefficients de corr\u00e9lation. On obtient ces coefficients gr\u00e2ce \u00e0 la fonction <b>dimdesc().<\/b><\/p>\n<pre><code><br \/>dimdesc(res_pca)<br \/> <\/code><\/pre>\n<p>\u00a0<\/p>\n","protected":false},"excerpt":{"rendered":"<p>La fonction PCA() permet d\u2019effectuer une ACP. library(FactoMineR) res_pca &lt;- PCA (iris, quali.sup=5) #On r\u00e9alise une ACP sur les 4 variables quantitatives du jeu de donn\u00e9es iris #La 5\u00e8me variable qui correspond au nom de la vari\u00e9t\u00e9 est qualitative #Nous pla\u00e7ons cette variable en suppl\u00e9mentaire, #cette variable ne participera donc pas \u00e0 la construction de l\u2019ACP, #mais elle apportera de l\u2019information suppl\u00e9mentaire \u00a0 plot.PCA(res_pca,col.quali=\u00a0\u00bbblue\u00a0\u00bb, label=\u00a0\u00bbquali\u00a0\u00bb) #La fonction plot.PCA contient de nombreux param\u00e8tres modulables #ici nous choisissons la couleur de la variable qualitative #et de cacher l\u2019\u00e9tiquette des individus gr\u00e2ce au param\u00e8tre \u00ab\u00a0label\u00a0\u00bb \u00a0 Pour pouvoir d\u00e9crire les r\u00e9sultats de cette analyse nous avons besoin d\u2019\u00e9tudier<a class=\"more-link\" href=\"https:\/\/thinkr.fr\/abcdr\/comment-faire-une-analyse-en-composantes-principale-acp-sur-r-pca-plot-pca\/\">Read More &rarr;<\/a><\/p>\n","protected":false},"author":13,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"content-type":"","rop_custom_images_group":[],"rop_custom_messages_group":[],"rop_publish_now":"initial","rop_publish_now_accounts":{"twitter_399453572_399453572":""},"rop_publish_now_history":[],"rop_publish_now_status":"pending","_jetpack_newsletter_access":"","_jetpack_dont_email_post_to_subs":false,"_jetpack_newsletter_tier_id":0,"_jetpack_memberships_contains_paywalled_content":false,"_jetpack_memberships_contains_paid_content":false,"footnotes":"","jetpack_post_was_ever_published":false},"categories":[8,12],"tags":[],"class_list":{"0":"entry","1":"post","2":"publish","3":"author-helene","4":"post-3210","6":"format-standard","7":"category-fonctions-utiles","8":"category-manipulation-de-donnees"},"acf":[],"jetpack_featured_media_url":"","jetpack_shortlink":"https:\/\/wp.me\/p9O7Sx-PM","jetpack_sharing_enabled":true,"_links":{"self":[{"href":"https:\/\/thinkr.fr\/abcdr\/wp-json\/wp\/v2\/posts\/3210","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/thinkr.fr\/abcdr\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/thinkr.fr\/abcdr\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/thinkr.fr\/abcdr\/wp-json\/wp\/v2\/users\/13"}],"replies":[{"embeddable":true,"href":"https:\/\/thinkr.fr\/abcdr\/wp-json\/wp\/v2\/comments?post=3210"}],"version-history":[{"count":2,"href":"https:\/\/thinkr.fr\/abcdr\/wp-json\/wp\/v2\/posts\/3210\/revisions"}],"predecessor-version":[{"id":4303,"href":"https:\/\/thinkr.fr\/abcdr\/wp-json\/wp\/v2\/posts\/3210\/revisions\/4303"}],"wp:attachment":[{"href":"https:\/\/thinkr.fr\/abcdr\/wp-json\/wp\/v2\/media?parent=3210"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/thinkr.fr\/abcdr\/wp-json\/wp\/v2\/categories?post=3210"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/thinkr.fr\/abcdr\/wp-json\/wp\/v2\/tags?post=3210"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}