{"id":1574,"date":"2023-07-25T19:42:15","date_gmt":"2023-07-25T19:42:15","guid":{"rendered":"https:\/\/statorials.org\/ko\/r%e1%84%8b%e1%85%b4-%e1%84%92%e1%85%a2%e1%86%bc%e1%84%85%e1%85%a7%e1%86%af-%e1%84%92%e1%85%a9%e1%86%ab%e1%84%83%e1%85%a9%e1%86%bc\/"},"modified":"2023-07-25T19:42:15","modified_gmt":"2023-07-25T19:42:15","slug":"r%e1%84%8b%e1%85%b4-%e1%84%92%e1%85%a2%e1%86%bc%e1%84%85%e1%85%a7%e1%86%af-%e1%84%92%e1%85%a9%e1%86%ab%e1%84%83%e1%85%a9%e1%86%bc","status":"publish","type":"post","link":"https:\/\/statorials.org\/ko\/r%e1%84%8b%e1%85%b4-%e1%84%92%e1%85%a2%e1%86%bc%e1%84%85%e1%85%a7%e1%86%af-%e1%84%92%e1%85%a9%e1%86%ab%e1%84%83%e1%85%a9%e1%86%bc\/","title":{"rendered":"R\uc5d0\uc11c \ud63c\ub3d9 \ud589\ub82c\uc744 \ub9cc\ub4dc\ub294 \ubc29\ubc95(\ub2e8\uacc4\ubcc4)"},"content":{"rendered":"<p><\/p>\n<hr>\n<p><span style=\"color: #000000;\"><a href=\"https:\/\/statorials.org\/ko\/\u1105\u1169\u110c\u1175\u1109\u1173\u1110\u1175\u11a8-\u1112\u116c\u1100\u1171-1\/\" target=\"_blank\" rel=\"noopener\">\ub85c\uc9c0\uc2a4\ud2f1 \ud68c\uadc0<\/a> \ub294 \uc751\ub2f5 \ubcc0\uc218\uac00 \uc774\uc9c4\uc77c \ub54c \uc0ac\uc6a9\ud560 \uc218 \uc788\ub294 \ud68c\uadc0 \uc720\ud615\uc785\ub2c8\ub2e4.<\/span><\/p>\n<p> <span style=\"color: #000000;\">\ub85c\uc9c0\uc2a4\ud2f1 \ud68c\uadc0 \ubaa8\ub378\uc758 \ud488\uc9c8\uc744 \ud3c9\uac00\ud558\ub294 \uc77c\ubc18\uc801\uc778 \ubc29\ubc95\uc740 \ubaa8\ub378\uc758 \uc608\uce21 \uac12\uacfc \ud14c\uc2a4\ud2b8 \ub370\uc774\ud130 \uc138\ud2b8\uc758 \uc2e4\uc81c \uac12\uc744 \ubcf4\uc5ec\uc8fc\ub294 2\u00d72 \ud14c\uc774\ube14\uc778 <strong>\ud63c\ub3d9 \ud589\ub82c\uc744<\/strong> \ub9cc\ub4dc\ub294 \uac83\uc785\ub2c8\ub2e4.<\/span> <\/p>\n<p><img decoding=\"async\" loading=\"lazy\" class=\" wp-image-15654 aligncenter\" src=\"https:\/\/statorials.org\/wp-content\/uploads\/2023\/08\/confusionr1.png\" alt=\"\" width=\"292\" height=\"129\" srcset=\"\" sizes=\"auto, \"><\/p>\n<p> <span style=\"color: #000000;\">\ub2e4\uc74c \ub2e8\uacc4\ubcc4 \uc608\uc81c\uc5d0\uc11c\ub294 R\uc5d0\uc11c \ud63c\ub3d9 \ud589\ub82c\uc744 \ub9cc\ub4dc\ub294 \ubc29\ubc95\uc744 \ubcf4\uc5ec\uc90d\ub2c8\ub2e4.<\/span><\/p>\n<h3> <span style=\"color: #000000;\"><strong>1\ub2e8\uacc4: \ub85c\uc9c0\uc2a4\ud2f1 \ud68c\uadc0 \ubaa8\ub378 \uc801\ud569<\/strong><\/span><\/h3>\n<p> <span style=\"color: #000000;\">\uc774 \uc608\uc5d0\uc11c\ub294 <strong>ISLR<\/strong> \ud328\ud0a4\uc9c0\uc758 <strong>\uae30\ubcf8<\/strong> \ub370\uc774\ud130 \uc138\ud2b8\ub97c \uc0ac\uc6a9\ud569\ub2c8\ub2e4. \uc6b0\ub9ac\ub294 \ud559\uc0dd \uc0c1\ud0dc, \uc740\ud589 \uc794\uace0 \ubc0f \uc5f0\uac04 \uc18c\ub4dd\uc744 \uc0ac\uc6a9\ud558\uc5ec \ud2b9\uc815 \uac1c\uc778\uc774 \ub300\ucd9c\uc744 \ubd88\uc774\ud589\ud560 \uac00\ub2a5\uc131\uc744 \uc608\uce21\ud569\ub2c8\ub2e4.<\/span><\/p>\n<p> <span style=\"color: #000000;\">\ub2e4\uc74c \ucf54\ub4dc\ub294 \ub85c\uc9c0\uc2a4\ud2f1 \ud68c\uadc0 \ubaa8\ub378\uc744 \uc774 \ub370\uc774\ud130 \uc138\ud2b8\uc5d0 \ub9de\ucd94\ub294 \ubc29\ubc95\uc744 \ubcf4\uc5ec\uc90d\ub2c8\ub2e4.<\/span><\/p>\n<pre style=\"background-color: #ececec; font-size: 15px;\"> <strong><span style=\"color: #008080;\">#load necessary packages\n<\/span><span style=\"color: #993300;\">library<\/span> (caret)\n<span style=\"color: #993300;\">library<\/span> (InformationValue)\n<span style=\"color: #993300;\">library<\/span> (ISLR)\n\n<span style=\"color: #008080;\">#load dataset\n<\/span>data &lt;-Default\n\n<span style=\"color: #008080;\">#split dataset into training and testing set\n<\/span>set. <span style=\"color: #3366ff;\">seeds<\/span> (1)\nsample &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)\n<\/strong><\/pre>\n<h3> <span style=\"color: #000000;\"><strong>2\ub2e8\uacc4: \ud63c\ub3d9 \ud589\ub82c \ub9cc\ub4e4\uae30<\/strong><\/span><\/h3>\n<p> <span style=\"color: #000000;\">\ub2e4\uc74c\uc73c\ub85c <strong>\uce90\ub7ff<\/strong> \ud328\ud0a4\uc9c0\uc758 <strong>ConfusionMatrix()<\/strong> \ud568\uc218\ub97c \uc0ac\uc6a9\ud558\uc5ec \ud63c\ub3d9 \ud589\ub82c\uc744 \ub9cc\ub4ed\ub2c8\ub2e4.<\/span><\/p>\n<pre style=\"background-color: #ececec; font-size: 15px;\"> <strong><span style=\"color: #008080;\">#use model to predict probability of default\n<span style=\"color: #000000;\">predicted &lt;- predict(model, test, type=\"response\")\n<\/span>\n#convert defaults from \"Yes\" and \"No\" to 1's and 0's\n<span style=\"color: #000000;\">test$default &lt;- ifelse(test$default==\" <span style=\"color: #008000;\">Yes<\/span> \", 1, 0)\n<\/span>\n#find optimal cutoff probability to use to maximize accuracy\n<span style=\"color: #000000;\">optimal &lt;- optimalCutoff(test$default, predicted)[1]\n<\/span>\n#create confusion matrix\n<span style=\"color: #000000;\">confusionMatrix(test$default, predicted)\n\n     0 1\n0 2912 64\n1 21 39\n<\/span><\/span><\/strong><\/pre>\n<h3> <span style=\"color: #000000;\"><strong>3\ub2e8\uacc4: \ud63c\ub3d9 \ud589\ub82c \ud3c9\uac00<\/strong><\/span><\/h3>\n<p> <span style=\"color: #000000;\">\ud63c\ub3d9 \ud589\ub82c\uc744 \uc0ac\uc6a9\ud558\uc5ec \ub2e4\uc74c \uce21\uc815\ud56d\ubaa9\uc744 \uacc4\uc0b0\ud560 \uc218\ub3c4 \uc788\uc2b5\ub2c8\ub2e4.<\/span><\/p>\n<ul>\n<li> <span style=\"color: #000000;\"><strong>\ubbfc\uac10\ub3c4:<\/strong> &#8220;\uc2e4\uc81c \uc591\uc131\ub960&#8221; &#8211; \ubaa8\ub378\uc774 \ucc44\ubb34 \ubd88\uc774\ud589\uc744 \uc815\ud655\ud558\uac8c \uc608\uce21\ud55c \uac1c\uc778\uc758 \ube44\uc728\uc785\ub2c8\ub2e4.<\/span><\/li>\n<li> <span style=\"color: #000000;\"><strong>\ud2b9\uc774\uc131:<\/strong> &#8220;\uc9c4\uc74c\uc131 \ube44\uc728&#8221; &#8211; \ubaa8\ub378\uc774 \uc62c\ubc14\ub974\uac8c \uc608\uce21\ud55c \uac1c\uc778\uc758 \ube44\uc728\uc774 \uae30\ubcf8\uac12\uc774 <em>\uc544\ub2d9\ub2c8\ub2e4<\/em> .<\/span><\/li>\n<li> <span style=\"color: #000000;\"><strong>\ucd1d \uc624\ubd84\ub958\uc728:<\/strong> \ubaa8\ub378\uc5d0 \uc758\ud574 \ubc1c\uc0dd\ud55c \ucd1d \uc624\ubd84\ub958 \ube44\uc728\uc785\ub2c8\ub2e4.<\/span><\/li>\n<\/ul>\n<p> <span style=\"color: #000000;\">\ub2e4\uc74c \ucf54\ub4dc\ub294 \uc774\ub7ec\ud55c \uce21\uc815\ud56d\ubaa9\uc744 \uacc4\uc0b0\ud558\ub294 \ubc29\ubc95\uc744 \ubcf4\uc5ec\uc90d\ub2c8\ub2e4.<\/span><\/p>\n<pre style=\"background-color: #ececec; font-size: 15px;\"> <span style=\"color: #000000;\"><strong><span style=\"color: #008080;\">#calculate sensitivity<\/span>\nsensitivity(test$default, predicted)\n\n[1] 0.3786408\n\n<span style=\"color: #008080;\">#calculate specificity\n<\/span>specificity(test$default, predicted)\n\n[1] 0.9928401\n\n<span style=\"color: #008080;\">#calculate total misclassification error rate\n<\/span>misClassError(test$default, predicted, <span style=\"color: #3366ff;\">threshold<\/span> =optimal)\n\n[1] 0.027<\/strong><\/span><\/pre>\n<p> <span style=\"color: #000000;\">\uc774 \ubaa8\ub378\uc758 \ucd1d \ubd84\ub958 \uc624\ub958\uc728\uc740 <strong>2.7%<\/strong> \uc785\ub2c8\ub2e4.<\/span><\/p>\n<p> <span style=\"color: #000000;\">\uc77c\ubc18\uc801\uc73c\ub85c \uc774 \ube44\uc728\uc774 \ub0ae\uc744\uc218\ub85d \ubaa8\ub378\uc774 \uacb0\uacfc\ub97c \ub354 \uc798 \uc608\uce21\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4. \ub530\ub77c\uc11c \uc774 \ud2b9\uc815 \ubaa8\ub378\uc740 \uac1c\uc778\uc758 \ucc44\ubb34 \ubd88\uc774\ud589 \uc5ec\ubd80\ub97c \uc608\uce21\ud558\ub294 \ub370 \ub9e4\uc6b0 \ud6a8\uacfc\uc801\uc778 \uac83\uc73c\ub85c \uc785\uc99d\ub418\uc5c8\uc2b5\ub2c8\ub2e4.<\/span><\/p>\n","protected":false},"excerpt":{"rendered":"<p>\ub85c\uc9c0\uc2a4\ud2f1 \ud68c\uadc0 \ub294 \uc751\ub2f5 \ubcc0\uc218\uac00 \uc774\uc9c4\uc77c \ub54c \uc0ac\uc6a9\ud560 \uc218 \uc788\ub294 \ud68c\uadc0 \uc720\ud615\uc785\ub2c8\ub2e4. \ub85c\uc9c0\uc2a4\ud2f1 \ud68c\uadc0 \ubaa8\ub378\uc758 \ud488\uc9c8\uc744 \ud3c9\uac00\ud558\ub294 \uc77c\ubc18\uc801\uc778 \ubc29\ubc95\uc740 \ubaa8\ub378\uc758 \uc608\uce21 \uac12\uacfc \ud14c\uc2a4\ud2b8 \ub370\uc774\ud130 \uc138\ud2b8\uc758 \uc2e4\uc81c \uac12\uc744 \ubcf4\uc5ec\uc8fc\ub294 2\u00d72 \ud14c\uc774\ube14\uc778 \ud63c\ub3d9 \ud589\ub82c\uc744 \ub9cc\ub4dc\ub294 \uac83\uc785\ub2c8\ub2e4. \ub2e4\uc74c \ub2e8\uacc4\ubcc4 \uc608\uc81c\uc5d0\uc11c\ub294 R\uc5d0\uc11c \ud63c\ub3d9 \ud589\ub82c\uc744 \ub9cc\ub4dc\ub294 \ubc29\ubc95\uc744 \ubcf4\uc5ec\uc90d\ub2c8\ub2e4. 1\ub2e8\uacc4: \ub85c\uc9c0\uc2a4\ud2f1 \ud68c\uadc0 \ubaa8\ub378 \uc801\ud569 \uc774 \uc608\uc5d0\uc11c\ub294 ISLR \ud328\ud0a4\uc9c0\uc758 \uae30\ubcf8 \ub370\uc774\ud130 \uc138\ud2b8\ub97c [&hellip;]<\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[20],"tags":[],"class_list":["post-1574","post","type-post","status-publish","format-standard","hentry","category-20"],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v21.5 - https:\/\/yoast.com\/wordpress\/plugins\/seo\/ -->\n<title>R\uc5d0\uc11c \ud63c\ub3d9 \ud589\ub82c\uc744 \ub9cc\ub4dc\ub294 \ubc29\ubc95(\ub2e8\uacc4\ubcc4)<\/title>\n<meta name=\"description\" content=\"\uc774 \ud29c\ud1a0\ub9ac\uc5bc\uc5d0\uc11c\ub294 \ub2e8\uacc4\ubcc4 \uc608\uc81c\ub97c \ud3ec\ud568\ud558\uc5ec R\uc5d0\uc11c \ud63c\ub3d9 \ud589\ub82c\uc744 \ub9cc\ub4dc\ub294 \ubc29\ubc95\uc744 \uc124\uba85\ud569\ub2c8\ub2e4.\" \/>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" 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