{"id":3622,"date":"2023-07-16T12:08:13","date_gmt":"2023-07-16T12:08:13","guid":{"rendered":"https:\/\/statorials.org\/cn\/r%e4%b8%ad%e7%9a%84%e8%82%98%e9%83%a8%e6%96%b9%e6%b3%95\/"},"modified":"2023-07-16T12:08:13","modified_gmt":"2023-07-16T12:08:13","slug":"r%e4%b8%ad%e7%9a%84%e8%82%98%e9%83%a8%e6%96%b9%e6%b3%95","status":"publish","type":"post","link":"https:\/\/statorials.org\/cn\/r%e4%b8%ad%e7%9a%84%e8%82%98%e9%83%a8%e6%96%b9%e6%b3%95\/","title":{"rendered":"\u5982\u4f55\u5728r\u4e2d\u4f7f\u7528elbow\u65b9\u6cd5\u5bfb\u627e\u6700\u4f18\u7c07"},"content":{"rendered":"<p><\/p>\n<hr>\n<p><span style=\"color: #000000;\"><a href=\"https:\/\/statorials.org\/cn\/\u7edf\u8ba1\u5b66\u4ee5\u7b80\u5355\u76f4\u63a5\u7684\u65b9\u5f0f\u89e3\u91ca\u6982\u5ff5\uff0c\u6211\u4eec\u4f7f\u5b66\u4e60\u7edf\u8ba1\u53d8\u5f97\u66f4\u5bb9\u6613\/\" target=\"_blank\" rel=\"noopener\">\u673a\u5668\u5b66\u4e60<\/a>\u4e2d\u6700\u5e38\u7528\u7684\u805a\u7c7b\u7b97\u6cd5\u4e4b\u4e00\u79f0\u4e3a<strong>k \u5747\u503c\u805a\u7c7b<\/strong>\u3002<\/span><\/p>\n<p> <span style=\"color: #000000;\">K \u5747\u503c\u805a\u7c7b\u662f\u4e00\u79cd\u5c06\u6570\u636e\u96c6\u4e2d\u7684\u6bcf\u4e2a\u89c2\u5bdf\u7ed3\u679c\u653e\u5165<em>K<\/em>\u4e2a\u805a\u7c7b\u4e2d\u7684\u4e00\u4e2a\u6280\u672f\u3002<\/span><\/p>\n<p><span style=\"color: #000000;\">\u6700\u7ec8\u76ee\u6807\u662f\u62e5\u6709<em>K \u4e2a<\/em>\u7c07\uff0c\u5176\u4e2d\u6bcf\u4e2a\u7c07\u5185\u7684\u89c2\u5bdf\u7ed3\u679c\u5f7c\u6b64\u975e\u5e38\u76f8\u4f3c\uff0c\u800c\u4e0d\u540c\u7c07\u4e2d\u7684\u89c2\u5bdf\u7ed3\u679c\u5f7c\u6b64\u975e\u5e38\u4e0d\u540c\u3002<\/span><\/p>\n<p><span style=\"color: #000000;\">\u5728\u8fdb\u884c k \u5747\u503c\u805a\u7c7b\u65f6\uff0c\u7b2c\u4e00\u6b65\u662f\u9009\u62e9<em>K<\/em>\u503c\u2014\u2014\u6211\u4eec\u60f3\u8981\u5c06\u89c2\u6d4b\u503c\u653e\u5165\u7684\u805a\u7c7b\u6570\u91cf\u3002<\/span><\/p>\n<p><span style=\"color: #000000;\">\u9009\u62e9<em>K<\/em>\u503c\u7684\u6700\u5e38\u89c1\u65b9\u6cd5\u4e4b\u4e00\u79f0\u4e3a<strong>\u8098\u6cd5<\/strong>\uff0c\u8be5\u65b9\u6cd5\u6d89\u53ca\u521b\u5efa\u4e00\u4e2a\u56fe\uff0c\u5176\u4e2d x \u8f74\u4e3a\u7c07\u6570\uff0cy \u8f74\u4e3a\u5e73\u65b9\u548c\u603b\u6570\uff0c\u7136\u540e\u786e\u5b9a\u56fe\u4e2d\u51fa\u73b0\u201c\u819d\u76d6\u201d\u6216\u8f6c\u5f2f\u7684\u5730\u65b9\u3002<\/span><\/p>\n<p> <span style=\"color: #000000;\">x \u8f74\u4e0a\u51fa\u73b0\u201c\u62d0\u70b9\u201d\u7684\u70b9\u544a\u8bc9\u6211\u4eec\u5728 k \u5747\u503c\u805a\u7c7b\u7b97\u6cd5\u4e2d\u4f7f\u7528\u7684\u6700\u4f73\u805a\u7c7b\u6570\u91cf\u3002<\/span><\/p>\n<p><span style=\"color: #000000;\">\u4ee5\u4e0b\u793a\u4f8b\u5c55\u793a\u4e86\u5982\u4f55\u5728 R \u4e2d\u4f7f\u7528\u8098\u90e8\u65b9\u6cd5\u3002<\/span><\/p>\n<h2><span style=\"color: #000000;\"><strong>\u793a\u4f8b\uff1a\u5728 R \u4e2d\u4f7f\u7528\u8098\u90e8\u65b9\u6cd5<\/strong><\/span><\/h2>\n<p><span style=\"color: #000000;\">\u5728\u672c\u4f8b\u4e2d\uff0c\u6211\u4eec\u5c06\u4f7f\u7528 R \u4e2d\u5185\u7f6e\u7684<strong>USArrests<\/strong>\u6570\u636e\u96c6\uff0c\u5176\u4e2d\u5305\u542b 1973 \u5e74\u7f8e\u56fd\u5404\u5dde\u6bcf 10 \u4e07\u4eba\u56e0\u8c0b\u6740\u3001\u88ad\u51fb\u548c\u5f3a\u5978\u800c\u88ab\u6355\u7684\u4eba\u6570\uff0c\u4ee5\u53ca\u6bcf\u4e2a\u5dde\u5c45\u4f4f\u5728\u57ce\u5e02\u7684\u4eba\u53e3\u767e\u5206\u6bd4\u5730\u533a\u3002 \uff0c\u57ce\u5e02\u6d41\u884c\u97f3\u4e50\u3002<\/span><\/p>\n<p><span style=\"color: #000000;\">\u4ee5\u4e0b\u4ee3\u7801\u6f14\u793a\u5982\u4f55\u52a0\u8f7d\u6570\u636e\u96c6\u3001\u5220\u9664\u7f3a\u5931\u503c\u7684\u884c\u4ee5\u53ca\u7f29\u653e\u6570\u636e\u96c6\u4e2d\u7684\u6bcf\u4e2a\u53d8\u91cf\u4ee5\u4f7f\u5176\u5e73\u5747\u503c\u4e3a 0\u3001\u6807\u51c6\u5dee\u4e3a 1\uff1a<\/span><\/p>\n<pre style=\"background-color: #ececec; font-size: 15px;\"> <strong><span style=\"color: #008080;\">#load data<\/span>\ndf &lt;-USArrests\n\n<span style=\"color: #008080;\">#remove rows with missing values<\/span><\/strong>\n<strong>df &lt;- na. <span style=\"color: #3366ff;\">omitted<\/span> (df)\n\n<span style=\"color: #008080;\">#scale each variable to have a mean of 0 and sd of 1<\/span><\/strong>\n<strong>df &lt;- scale(df)\n\n<span style=\"color: #008080;\">#view first six rows of dataset<\/span>\nhead(df)\n\n               Murder Assault UrbanPop Rape\nAlabama 1.24256408 0.7828393 -0.5209066 -0.003416473\nAlaska 0.50786248 1.1068225 -1.2117642 2.484202941\nArizona 0.07163341 1.4788032 0.9989801 1.042878388\nArkansas 0.23234938 0.2308680 -1.0735927 -0.184916602\nCalifornia 0.27826823 1.2628144 1.7589234 2.067820292\nColorado 0.02571456 0.3988593 0.8608085 1.864967207\n<\/strong><\/pre>\n<p><span style=\"color: #000000;\">\u4e3a\u4e86\u627e\u5230 k-means \u7b97\u6cd5\u4e2d\u4f7f\u7528\u7684\u6700\u4f73\u7c07\u6570\uff0c\u6211\u4eec\u5c06\u4f7f\u7528<strong>factoextra<\/strong>\u5305\u4e2d\u7684<strong>fviz_nbclust()<\/strong>\u51fd\u6570\u6765\u521b\u5efa\u7c07\u6570\u4e0e\u5e73\u65b9\u548c\u603b\u6570\u7684\u5173\u7cfb\u56fe\uff1a<\/span> <\/p>\n<pre style=\"background-color: #ececec; font-size: 15px;\"> <strong><span style=\"color: #008000;\">library<\/span> (cluster)\n<span style=\"color: #008000;\">library<\/span> (factoextra)\n\n<span style=\"color: #008080;\">#create plot of number of clusters vs total within sum of squares<\/span>\nfviz_nbclust(df, kmeans, method = \u201c <span style=\"color: #ff0000;\">wss<\/span> \u201d)<\/strong> <\/pre>\n<p><img decoding=\"async\" loading=\"lazy\" class=\"aligncenter wp-image-12310\" src=\"https:\/\/statorials.org\/wp-content\/uploads\/2023\/08\/kmmoyenne1.png\" alt=\"R\u5f2f\u66f2\u6cd5\" width=\"444\" height=\"434\" srcset=\"\" sizes=\"auto, \"><\/p>\n<p><span style=\"color: #000000;\">\u5728\u6b64\u56fe\u4e2d\uff0c\u4f3c\u4e4e\u5728 k = 4 \u4e2a\u7c07\u5904\u5b58\u5728\u201c\u62d0\u70b9\u201d\u6216\u626d\u7ed3\u3002\u8fd9\u662f\u5e73\u65b9\u548c\u4e2d\u7684\u603b\u6570\u5f00\u59cb\u7a33\u5b9a\u7684\u70b9\u3002<\/span><\/p>\n<p><span style=\"color: #000000;\">\u8fd9\u544a\u8bc9\u6211\u4eec k \u5747\u503c\u7b97\u6cd5\u4e2d\u4f7f\u7528\u7684\u6700\u4f73\u7c07\u6570\u662f 4\u3002<\/span><\/p>\n<p><span style=\"color: #000000;\"><strong>\u6ce8\u610f<\/strong>\uff1a\u867d\u7136\u901a\u8fc7\u4f7f\u7528\u66f4\u591a\u7684\u7c07\u6211\u4eec\u53ef\u80fd\u4f1a\u5f97\u5230\u66f4\u4f4e\u7684\u5e73\u65b9\u548c\u603b\u6570\uff0c\u4f46\u6211\u4eec<a href=\"https:\/\/statorials.org\/cn\/\u673a\u5668\u5b66\u4e60\u8fc7\u5ea6\u62df\u5408\/\" target=\"_blank\" rel=\"noopener\">\u53ef\u80fd\u4f1a\u8fc7\u5ea6\u62df\u5408\u8bad\u7ec3\u6570\u636e<\/a>\uff0c\u56e0\u6b64 k \u5747\u503c\u7b97\u6cd5\u5728\u6d4b\u8bd5\u6570\u636e\u4e0a\u6548\u679c\u4e0d\u4f73\u3002<\/span><\/p>\n<p><span style=\"color: #000000;\">\u6211\u4eec\u53ef\u4ee5\u4f7f\u7528<strong>cluster<\/strong>\u5305\u4e2d\u7684<strong>kmeans()<\/strong>\u51fd\u6570\uff0c\u4f7f\u7528<em>k<\/em>\u7684\u6700\u4f73\u503c 4 \u5bf9\u6570\u636e\u96c6\u6267\u884c k \u5747\u503c\u805a\u7c7b\uff1a<\/span><\/p>\n<pre style=\"background-color: #ececec; font-size: 15px;\"> <strong><span style=\"color: #008080;\">#make this example reproducible\n<span style=\"color: #000000;\">set. <span style=\"color: #3366ff;\">seeds<\/span> (1)<\/span>\n\n#perform k-means clustering with k = 4 clusters\n<\/span>km &lt;- kmeans(df, centers = 4, nstart = 25)\n\n<span style=\"color: #008080;\">#view results\n<\/span>km\n\nK-means clustering with 4 clusters of sizes 16, 13, 13, 8\n\nCluster means:\n      Murder Assault UrbanPop Rape\n1 -0.4894375 -0.3826001 0.5758298 -0.26165379\n2 -0.9615407 -1.1066010 -0.9301069 -0.96676331\n3 0.6950701 1.0394414 0.7226370 1.27693964\n4 1.4118898 0.8743346 -0.8145211 0.01927104\n\nVector clustering:\n       Alabama Alaska Arizona Arkansas California Colorado \n             4 3 3 4 3 3 \n   Connecticut Delaware Florida Georgia Hawaii Idaho \n             1 1 3 4 1 2 \n      Illinois Indiana Iowa Kansas Kentucky Louisiana \n             3 1 2 1 2 4 \n         Maine Maryland Massachusetts Michigan Minnesota Mississippi \n             2 3 1 3 2 4 \n      Missouri Montana Nebraska Nevada New Hampshire New Jersey \n             3 2 2 3 2 1 \n    New Mexico New York North Carolina North Dakota Ohio Oklahoma \n             3 3 4 2 1 1 \n        Oregon Pennsylvania Rhode Island South Carolina South Dakota Tennessee \n             1 1 1 4 2 4 \n         Texas Utah Vermont Virginia Washington West Virginia \n             3 1 2 1 1 2 \n     Wisconsin Wyoming \n             2 1 \n\nWithin cluster sum of squares by cluster:\n[1] 16.212213 11.952463 19.922437 8.316061\n (between_SS \/ total_SS = 71.2%)\n\nAvailable components:\n\n[1] \"cluster\" \"centers\" \"totss\" \"withinss\" \"tot.withinss\" \"betweenss\"   \n[7] \"size\" \"iter\" \"ifault\"         \n<\/strong><\/pre>\n<p><span style=\"color: #000000;\">\u4ece\u7ed3\u679c\u6211\u4eec\u53ef\u4ee5\u770b\u51fa\uff1a<\/span><\/p>\n<ul>\n<li> <span style=\"color: #000000;\"><b>16 \u4e2a<\/b>\u5dde\u88ab\u5206\u914d\u5230\u7b2c\u4e00\u4e2a\u96c6\u7fa4<\/span><\/li>\n<li><span style=\"color: #000000;\"><strong>13\u4e2a<\/strong>\u5dde\u5df2\u88ab\u5206\u914d\u5230\u7b2c\u4e8c\u4e2a\u96c6\u7fa4<\/span><\/li>\n<li><span style=\"color: #000000;\"><strong>13\u4e2a<\/strong>\u5dde\u5df2\u88ab\u5206\u914d\u5230\u7b2c\u4e09\u96c6\u7fa4<\/span><\/li>\n<li><span style=\"color: #000000;\"><b>8\u4e2a<\/b>\u5dde\u5df2\u88ab\u5206\u914d\u5230\u7b2c\u56db\u96c6\u7fa4<\/span><\/li>\n<\/ul>\n<p><span style=\"color: #000000;\">\u6211\u4eec\u8fd8\u53ef\u4ee5\u5c06\u6bcf\u4e2a\u72b6\u6001\u7684\u805a\u7c7b\u5206\u914d\u6dfb\u52a0\u5230\u539f\u59cb\u6570\u636e\u96c6\u4e2d\uff1a<\/span><\/p>\n<pre style=\"background-color: #ececec; font-size: 15px;\"> <strong><span style=\"color: #008080;\">#add cluster assignment to original data\n<span style=\"color: #000000;\">final_data &lt;- cbind(USArrests, cluster = km$cluster)\n<\/span>\n#view final data\n<span style=\"color: #000000;\">head(final_data)\n\n\t<\/span><span style=\"color: #000000;\">Murder Assault UrbanPop<\/span> <span style=\"color: #000000;\">Rape<\/span> <span style=\"color: #000000;\">cluster\n\t\t\t\t\nAlabama<\/span> <span style=\"color: #000000;\">13.2<\/span> <span style=\"color: #000000;\">236 58<\/span> <span style=\"color: #000000;\">21.2<\/span> <span style=\"color: #000000;\">4\nAlaska<\/span> <span style=\"color: #000000;\">10.0 263 48<\/span> <span style=\"color: #000000;\">44.5<\/span> <span style=\"color: #000000;\">2\nArizona<\/span> <span style=\"color: #000000;\">8.1 294 80<\/span> <span style=\"color: #000000;\">31.0<\/span> <span style=\"color: #000000;\">2\nArkansas<\/span> <span style=\"color: #000000;\">8.8 190 50<\/span> <span style=\"color: #000000;\">19.5<\/span> <span style=\"color: #000000;\">4\nCalifornia<\/span> <span style=\"color: #000000;\">9.0 276 91<\/span> <span style=\"color: #000000;\">40.6<\/span> <span style=\"color: #000000;\">2\nColorado<\/span> <span style=\"color: #000000;\">7.9 204 78<\/span> <span style=\"color: #000000;\">38.7<\/span> <span style=\"color: #000000;\">2\n<\/span><\/span><\/strong><\/pre>\n<p><span style=\"color: #000000;\">\u539f\u59cb\u6570\u636e\u5e93\u4e2d\u7684\u6bcf\u4e2a\u89c2\u5bdf\u7ed3\u679c\u90fd\u88ab\u5206\u4e3a\u56db\u7ec4\u4e4b\u4e00\u3002<\/span><\/p>\n<h2><span style=\"color: #000000;\"><strong>\u5176\u4ed6\u8d44\u6e90<\/strong><\/span><\/h2>\n<p><span style=\"color: #000000;\">\u4ee5\u4e0b\u6559\u7a0b\u63d0\u4f9b\u4e86\u6709\u5173\u5982\u4f55\u5728 R \u4e2d\u8fd0\u884c\u5404\u79cd\u805a\u7c7b\u7b97\u6cd5\u7684\u5206\u6b65\u793a\u4f8b\uff1a<\/span><\/p>\n<p> <a href=\"https:\/\/statorials.org\/cn\/k-\u8868\u793a\u5728-r-\u4e2d\u5206\u7ec4\/\" target=\"_blank\" rel=\"noopener\">R \u4e2d\u7684 K \u5747\u503c\u805a\u7c7b\uff1a\u5206\u6b65\u793a\u4f8b<\/a><br \/><a href=\"https:\/\/statorials.org\/cn\/r-\u4e2d\u7684-k-\u4e2a\u4e2d\u5fc3\u70b9\/\" target=\"_blank\" rel=\"noopener\">R \u4e2d\u7684 K-Medoids \u805a\u7c7b\uff1a\u5206\u6b65\u793a\u4f8b<\/a><br \/>R \u4e2d\u7684\u5c42\u6b21\u805a\u7c7b\uff1a\u5206\u6b65\u793a\u4f8b<\/p>\n","protected":false},"excerpt":{"rendered":"<p>\u673a\u5668\u5b66\u4e60\u4e2d\u6700\u5e38\u7528\u7684\u805a\u7c7b\u7b97\u6cd5\u4e4b\u4e00\u79f0\u4e3ak \u5747\u503c\u805a\u7c7b\u3002 K \u5747\u503c\u805a\u7c7b\u662f\u4e00\u79cd\u5c06\u6570\u636e\u96c6\u4e2d\u7684\u6bcf\u4e2a\u89c2\u5bdf\u7ed3\u679c\u653e\u5165K\u4e2a\u805a\u7c7b\u4e2d\u7684\u4e00 [&hellip;]<\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[11],"tags":[],"class_list":["post-3622","post","type-post","status-publish","format-standard","hentry","category-11"],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v21.5 - https:\/\/yoast.com\/wordpress\/plugins\/seo\/ -->\n<title>\u5982\u4f55\u5728 R \u4e2d\u4f7f\u7528 Elbow \u65b9\u6cd5\u5bfb\u627e\u6700\u4f73\u7c07 - Statorials<\/title>\n<meta name=\"description\" content=\"\u672c\u6559\u7a0b\u4ecb\u7ecd\u5982\u4f55\u5728 R \u4e2d\u6267\u884c\u8098\u6cd5\u6765\u67e5\u627e\u805a\u7c7b\u7b97\u6cd5\u4e2d\u4f7f\u7528\u7684\u6700\u4f73\u805a\u7c7b\u6570\u3002\" \/>\n<meta name=\"robots\" content=\"index, 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