{"id":1583,"date":"2023-07-25T18:29:30","date_gmt":"2023-07-25T18:29:30","guid":{"rendered":"https:\/\/statorials.org\/ja\/r%e3%81%a6%e3%82%99%e3%81%af%e3%81%84%e3%81%84%e3%81%88\/"},"modified":"2023-07-25T18:29:30","modified_gmt":"2023-07-25T18:29:30","slug":"r%e3%81%a6%e3%82%99%e3%81%af%e3%81%84%e3%81%84%e3%81%88","status":"publish","type":"post","link":"https:\/\/statorials.org\/ja\/r%e3%81%a6%e3%82%99%e3%81%af%e3%81%84%e3%81%84%e3%81%88\/","title":{"rendered":"R \u3067 auc (\u66f2\u7dda\u4e0b\u9762\u7a4d) \u3092\u8a08\u7b97\u3059\u308b\u65b9\u6cd5"},"content":{"rendered":"<p><\/p>\n<hr>\n<p><span style=\"color: #000000;\"><a href=\"https:\/\/statorials.org\/ja\/\u30ed\u30b7\u3099\u30b9\u30c6\u30a3\u30c3\u30af\u56de\u5e30-1\/\" target=\"_blank\" rel=\"noopener noreferrer\">\u30ed\u30b8\u30b9\u30c6\u30a3\u30c3\u30af\u56de\u5e30\u306f\u3001<\/a>\u5fdc\u7b54\u5909\u6570\u304c\u30d0\u30a4\u30ca\u30ea\u306e\u5834\u5408\u306b\u56de\u5e30\u30e2\u30c7\u30eb\u3092\u8fd1\u4f3c\u3059\u308b\u305f\u3081\u306b\u4f7f\u7528\u3059\u308b\u7d71\u8a08\u624b\u6cd5\u3067\u3059\u3002\u30ed\u30b8\u30b9\u30c6\u30a3\u30c3\u30af\u56de\u5e30\u30e2\u30c7\u30eb\u304c\u30c7\u30fc\u30bf\u30bb\u30c3\u30c8\u306b\u3069\u306e\u7a0b\u5ea6\u9069\u5408\u3057\u3066\u3044\u308b\u304b\u3092\u8a55\u4fa1\u3059\u308b\u306b\u306f\u3001\u6b21\u306e 2 \u3064\u306e\u6307\u6a19\u3092\u78ba\u8a8d\u3057\u307e\u3059\u3002<\/span><\/p>\n<ul>\n<li><span style=\"color: #000000;\"><strong>\u611f\u5ea6:<\/strong>\u7d50\u679c\u304c\u5b9f\u969b\u306b\u80af\u5b9a\u7684\u306a\u5834\u5408\u306b\u3001\u30e2\u30c7\u30eb\u304c\u89b3\u6e2c\u5024\u306b\u5bfe\u3057\u3066\u80af\u5b9a\u7684\u306a\u7d50\u679c\u3092\u4e88\u6e2c\u3059\u308b\u78ba\u7387\u3002\u3053\u308c\u306f\u300c\u771f\u967d\u6027\u7387\u300d\u3068\u3082\u547c\u3070\u308c\u307e\u3059\u3002<\/span><\/li>\n<li><span style=\"color: #000000;\"><strong>\u7279\u7570\u6027:<\/strong>\u7d50\u679c\u304c\u5b9f\u969b\u306b\u306f\u9670\u6027\u3067\u3042\u308b\u5834\u5408\u306b\u3001\u30e2\u30c7\u30eb\u304c\u89b3\u6e2c\u5024\u306b\u5bfe\u3057\u3066\u9670\u6027\u306e\u7d50\u679c\u3092\u4e88\u6e2c\u3059\u308b\u78ba\u7387\u3002\u3053\u308c\u306f\u300c\u771f\u306e\u30cd\u30ac\u30c6\u30a3\u30d6\u7387\u300d\u3068\u3082\u547c\u3070\u308c\u307e\u3059\u3002<\/span><\/li>\n<\/ul>\n<p><span style=\"color: #000000;\">\u3053\u308c\u3089 2 \u3064\u306e\u6e2c\u5b9a\u5024\u3092\u8996\u899a\u5316\u3059\u308b 1 \u3064\u306e\u65b9\u6cd5\u306f\u3001\u300c\u53d7\u4fe1\u6a5f\u52d5\u4f5c\u7279\u6027\u300d\u66f2\u7dda\u3092\u8868\u3059<strong>ROC \u66f2\u7dda<\/strong>\u3092\u4f5c\u6210\u3059\u308b\u3053\u3068\u3067\u3059\u3002<\/span><\/p>\n<p><span style=\"color: #000000;\">\u3053\u308c\u306f\u3001\u611f\u5ea6\u3092 Y \u8ef8\u306b\u3001(1 \u2013 \u7279\u7570\u5ea6) \u3092 X \u8ef8\u306b\u793a\u3057\u305f\u30b0\u30e9\u30d5\u3067\u3059\u3002\u30c7\u30fc\u30bf\u306e\u5206\u985e\u306b\u304a\u3051\u308b\u30ed\u30b8\u30b9\u30c6\u30a3\u30c3\u30af\u56de\u5e30\u30e2\u30c7\u30eb\u306e\u6709\u52b9\u6027\u3092\u5b9a\u91cf\u5316\u3059\u308b 1 \u3064\u306e\u65b9\u6cd5\u306f\u3001\u300c\u66f2\u7dda\u306e\u4e0b\u306e\u9762\u7a4d\u300d\u3092\u8868\u3059<strong>AUC<\/strong>\u3092\u8a08\u7b97\u3059\u308b\u3053\u3068\u3067\u3059\u3002<\/span><\/p>\n<p> <span style=\"color: #000000;\">AUC \u304c 1 \u306b\u8fd1\u3065\u304f\u307b\u3069\u3001\u30e2\u30c7\u30eb\u306f\u512a\u308c\u3066\u3044\u307e\u3059\u3002<\/span><\/p>\n<p><span style=\"color: #000000;\">\u6b21\u306e\u6bb5\u968e\u7684\u306a\u4f8b\u306f\u3001R \u3067\u30ed\u30b8\u30b9\u30c6\u30a3\u30c3\u30af\u56de\u5e30\u30e2\u30c7\u30eb\u306e AUC \u3092\u8a08\u7b97\u3059\u308b\u65b9\u6cd5\u3092\u793a\u3057\u3066\u3044\u307e\u3059\u3002<\/span><\/p>\n<h3><span style=\"color: #000000;\"><strong>\u30b9\u30c6\u30c3\u30d7 1: \u30c7\u30fc\u30bf\u3092\u30ed\u30fc\u30c9\u3059\u308b<\/strong><\/span><\/h3>\n<p><span style=\"color: #000000;\">\u307e\u305a\u3001 <strong>ISLR<\/strong>\u30d1\u30c3\u30b1\u30fc\u30b8\u304b\u3089<strong>\u30c7\u30d5\u30a9\u30eb\u30c8\u306e<\/strong>\u30c7\u30fc\u30bf\u30bb\u30c3\u30c8\u3092\u8aad\u307f\u8fbc\u307f\u307e\u3059\u3002\u3053\u306e\u30c7\u30fc\u30bf\u30bb\u30c3\u30c8\u306b\u306f\u3001\u3055\u307e\u3056\u307e\u306a\u4eba\u3005\u304c\u30ed\u30fc\u30f3\u3092\u6ede\u7d0d\u3057\u305f\u304b\u3069\u3046\u304b\u306b\u95a2\u3059\u308b\u60c5\u5831\u304c\u542b\u307e\u308c\u3066\u3044\u307e\u3059\u3002<\/span><\/p>\n<pre style=\"background-color: #ececec; font-size: 15px;\"> <strong><span style=\"color: #008080;\">#load dataset\n<\/span>data &lt;- ISLR::Default\n\n<span style=\"color: #008080;\">#view first six rows of dataset\n<\/span>head(data)\n\n  default student balance income\n1 No No 729.5265 44361.625\n2 No Yes 817.1804 12106.135\n3 No No 1073.5492 31767.139\n4 No No 529.2506 35704.494\n5 No No 785.6559 38463.496\n6 No Yes 919.5885 7491.559\n<\/strong><\/pre>\n<h3><span style=\"color: #000000;\"><strong>\u30b9\u30c6\u30c3\u30d7 2: \u30ed\u30b8\u30b9\u30c6\u30a3\u30c3\u30af\u56de\u5e30\u30e2\u30c7\u30eb\u3092\u5f53\u3066\u306f\u3081\u308b<\/strong><\/span><\/h3>\n<p><span style=\"color: #000000;\">\u6b21\u306b\u3001\u30ed\u30b8\u30b9\u30c6\u30a3\u30c3\u30af\u56de\u5e30\u30e2\u30c7\u30eb\u3092\u5f53\u3066\u306f\u3081\u3066\u3001\u500b\u4eba\u304c\u50b5\u52d9\u4e0d\u5c65\u884c\u306b\u306a\u308b\u78ba\u7387\u3092\u4e88\u6e2c\u3057\u307e\u3059\u3002<\/span><\/p>\n<pre style=\"background-color: #ececec; font-size: 15px;\"> <strong><span style=\"color: #008080;\">#make this example reproducible\n<\/span>set. <span style=\"color: #3366ff;\">seeds<\/span> (1)\n\n<span style=\"color: #008080;\">#Use 70% of dataset as training set and remaining 30% as testing set\n<\/span>sample &lt;- sample(c(TRUE, FALSE), nrow(data), replace= <span style=\"color: #008000;\">TRUE<\/span> , prob=c(0.7,0.3))\ntrain &lt;- data[sample, ]\ntest &lt;- data[!sample, ] \n\n<span style=\"color: #008080;\">#fit logistic regression model\n<\/span>model &lt;- glm(default~student+balance+income, family=\" <span style=\"color: #008000;\">binomial<\/span> \", data=train)<\/strong><\/pre>\n<h3><span style=\"color: #000000;\"><strong>\u30b9\u30c6\u30c3\u30d7 3: \u30e2\u30c7\u30eb AUC \u3092\u8a08\u7b97\u3059\u308b<\/strong><\/span><\/h3>\n<p><span style=\"color: #000000;\">\u6b21\u306b\u3001 <strong>pROC<\/strong>\u30d1\u30c3\u30b1\u30fc\u30b8\u306e<strong>auc()<\/strong>\u95a2\u6570\u3092\u4f7f\u7528\u3057\u3066\u3001\u30e2\u30c7\u30eb\u306e AUC \u3092\u8a08\u7b97\u3057\u307e\u3059\u3002\u3053\u306e\u95a2\u6570\u306f\u6b21\u306e\u69cb\u6587\u3092\u4f7f\u7528\u3057\u307e\u3059\u3002<\/span><\/p>\n<p><strong><span style=\"color: #000000;\">\u306a\u3057(\u5fdc\u7b54\u3001\u4e88\u6e2c)<\/span><\/strong><\/p>\n<p><span style=\"color: #000000;\">\u3053\u306e\u4f8b\u3067\u3053\u306e\u95a2\u6570\u3092\u4f7f\u7528\u3059\u308b\u65b9\u6cd5\u306f\u6b21\u306e\u3068\u304a\u308a\u3067\u3059\u3002<\/span><\/p>\n<pre style=\"background-color: #ececec; font-size: 15px;\"> <strong><span style=\"color: #008080;\">#calculate probability of default for each individual in test dataset\n<\/span>predicted &lt;- predict(model, test, type=\" <span style=\"color: #008000;\">response<\/span> \")\n\n<span style=\"color: #008080;\">#calculate AUC\n<\/span><span style=\"color: #993300;\">library<\/span> (pROC)\nauc(test$default, predicted)\n\nSetting levels: control = No, case = Yes\nSetting direction: controls &lt; boxes\nArea under the curve: 0.9437\n<\/strong><\/pre>\n<p><span style=\"color: #000000;\">\u30e2\u30c7\u30eb\u306e AUC \u306f<strong>0.9437<\/strong>\u3067\u3042\u308b\u3053\u3068\u304c\u308f\u304b\u308a\u307e\u3059\u3002<\/span><\/p>\n<p><span style=\"color: #000000;\">\u3053\u306e\u5024\u306f 1 \u306b\u8fd1\u3044\u305f\u3081\u3001\u3053\u306e\u30e2\u30c7\u30eb\u304c\u500b\u4eba\u304c\u30ed\u30fc\u30f3\u3092\u6ede\u7d0d\u3059\u308b\u304b\u3069\u3046\u304b\u3092\u975e\u5e38\u306b\u3046\u307e\u304f\u4e88\u6e2c\u3057\u3066\u3044\u308b\u3053\u3068\u3092\u793a\u3057\u3066\u3044\u307e\u3059\u3002<\/span><\/p>\n","protected":false},"excerpt":{"rendered":"<p>\u30ed\u30b8\u30b9\u30c6\u30a3\u30c3\u30af\u56de\u5e30\u306f\u3001\u5fdc\u7b54\u5909\u6570\u304c\u30d0\u30a4\u30ca\u30ea\u306e\u5834\u5408\u306b\u56de\u5e30\u30e2\u30c7\u30eb\u3092\u8fd1\u4f3c\u3059\u308b\u305f\u3081\u306b\u4f7f\u7528\u3059\u308b\u7d71\u8a08\u624b\u6cd5\u3067\u3059\u3002\u30ed\u30b8\u30b9\u30c6\u30a3\u30c3\u30af\u56de\u5e30\u30e2\u30c7\u30eb\u304c\u30c7\u30fc\u30bf\u30bb\u30c3\u30c8\u306b\u3069\u306e\u7a0b\u5ea6\u9069\u5408\u3057\u3066\u3044\u308b\u304b\u3092\u8a55\u4fa1\u3059\u308b\u306b\u306f\u3001\u6b21\u306e 2 \u3064\u306e\u6307\u6a19\u3092\u78ba\u8a8d\u3057\u307e\u3059\u3002 \u611f\u5ea6:\u7d50\u679c\u304c [&hellip;]<\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[16],"tags":[],"class_list":["post-1583","post","type-post","status-publish","format-standard","hentry","category-16"],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v21.5 - https:\/\/yoast.com\/wordpress\/plugins\/seo\/ -->\n<title>R \u3067 AUC (\u66f2\u7dda\u4e0b\u9762\u7a4d) \u3092\u8a08\u7b97\u3059\u308b\u65b9\u6cd5 - Statology<\/title>\n<meta name=\"description\" content=\"\u3053\u306e\u30c1\u30e5\u30fc\u30c8\u30ea\u30a2\u30eb\u3067\u306f\u3001R \u3067 AUC (\u66f2\u7dda\u4e0b\u9762\u7a4d) \u3092\u8a08\u7b97\u3059\u308b\u65b9\u6cd5\u3092\u3001\u30b9\u30c6\u30c3\u30d7\u30d0\u30a4\u30b9\u30c6\u30c3\u30d7\u306e\u4f8b\u3092\u542b\u3081\u3066\u8aac\u660e\u3057\u307e\u3059\u3002\" \/>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, 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