{"id":1192,"date":"2023-07-27T08:19:55","date_gmt":"2023-07-27T08:19:55","guid":{"rendered":"https:\/\/statorials.org\/ko\/r%e1%84%8b%e1%85%b4-%e1%84%8f%e1%85%b3%e1%84%85%e1%85%a6%e1%84%89%e1%85%b3%e1%84%90%e1%85%b3-%e1%84%92%e1%85%ac%e1%84%80%e1%85%b1\/"},"modified":"2023-07-27T08:19:55","modified_gmt":"2023-07-27T08:19:55","slug":"r%e1%84%8b%e1%85%b4-%e1%84%8f%e1%85%b3%e1%84%85%e1%85%a6%e1%84%89%e1%85%b3%e1%84%90%e1%85%b3-%e1%84%92%e1%85%ac%e1%84%80%e1%85%b1","status":"publish","type":"post","link":"https:\/\/statorials.org\/ko\/r%e1%84%8b%e1%85%b4-%e1%84%8f%e1%85%b3%e1%84%85%e1%85%a6%e1%84%89%e1%85%b3%e1%84%90%e1%85%b3-%e1%84%92%e1%85%ac%e1%84%80%e1%85%b1\/","title":{"rendered":"R\uc758 \ub2a5\uc120 \ud68c\uadc0(\ub2e8\uacc4\ubcc4)"},"content":{"rendered":"<p><\/p>\n<hr>\n<p><span style=\"color: #000000;\"><a href=\"https:\/\/statorials.org\/ko\/\u1102\u1173\u11bc\u1109\u1165\u11ab\u110b\u1174-\u1112\u116c\u1100\u1171\/\" target=\"_blank\" rel=\"noopener noreferrer\">\ub2a5\ud615 \ud68c\uadc0\ub294<\/a> \ub370\uc774\ud130\uc5d0 <a href=\"https:\/\/statorials.org\/ko\/\u1103\u1161\u110c\u116e\u11bc\u1100\u1169\u11bc\u1109\u1165\u11ab\u1109\u1165\u11bc-\u1112\u116c\u1100\u1171\/\" target=\"_blank\" rel=\"noopener noreferrer\">\ub2e4\uc911 \uacf5\uc120\uc131\uc774<\/a> \uc874\uc7ac\ud560 \ub54c \ud68c\uadc0 \ubaa8\ub378\uc744 \uc801\ud569\uc2dc\ud0a4\ub294 \ub370 \uc0ac\uc6a9\ud560 \uc218 \uc788\ub294 \ubc29\ubc95\uc785\ub2c8\ub2e4.<\/span><\/p>\n<p> <span style=\"color: #000000;\">\uac04\ub2e8\ud788 \ub9d0\ud574\uc11c, \ucd5c\uc18c \uc81c\uacf1 \ud68c\uadc0\ub294 \uc794\ucc28 \uc81c\uacf1\ud569(RSS)\uc744 \ucd5c\uc18c\ud654\ud558\ub294 \uacc4\uc218 \ucd94\uc815\uac12\uc744 \ucc3e\uc73c\ub824\uace0 \uc2dc\ub3c4\ud569\ub2c8\ub2e4.<\/span><\/p>\n<p> <span style=\"color: #000000;\"><strong>RSS = \u03a3(y <sub>i<\/sub> \u2013 \u0177 <sub>i<\/sub> )2<\/strong><\/span><\/p>\n<p> <span style=\"color: #000000;\">\uae08:<\/span><\/p>\n<ul>\n<li> <span style=\"color: #000000;\"><strong>\u03a3<\/strong> : <em>\ud569\uacc4\ub97c<\/em> \uc758\ubbf8\ud558\ub294 \uadf8\ub9ac\uc2a4 \uae30\ud638<\/span><\/li>\n<li> <span style=\"color: #000000;\"><strong>y <sub>i<\/sub><\/strong> : <sup>i\ubc88\uc9f8<\/sup> \uad00\uce21\uac12\uc5d0 \ub300\ud55c \uc2e4\uc81c \uc751\ub2f5 \uac12<\/span><\/li>\n<li> <span style=\"color: #000000;\"><strong>\u0177 <sub>i<\/sub><\/strong> : \ub2e4\uc911\uc120\ud615\ud68c\uadc0\ubaa8\ub378\uc744 \uae30\ubc18\uc73c\ub85c \uc608\uce21\ub41c \ubc18\uc751\uac12<\/span><\/li>\n<\/ul>\n<p> <span style=\"color: #000000;\">\ubc18\ub300\ub85c, \ub2a5\uc120 \ud68c\uadc0\ub294 \ub2e4\uc74c\uc744 \ucd5c\uc18c\ud654\ud558\ub824\uace0 \ud569\ub2c8\ub2e4.<\/span><\/p>\n<p> <span style=\"color: #000000;\"><strong>RSS + \u03bb\u03a3\u03b2 <sub>j<\/sub> <sup>2<\/sup><\/strong><\/span><\/p>\n<p> <span style=\"color: #000000;\">\uc5ec\uae30\uc11c <em>j\ub294<\/em> 1\uc5d0\uc11c <em>p\uac1c\uc758<\/em> \uc608\uce21 \ubcc0\uc218\ub85c \uc774\ub3d9\ud558\uace0 \u03bb \u2265 0\uc785\ub2c8\ub2e4.<\/span><\/p>\n<p> <span style=\"color: #000000;\">\ubc29\uc815\uc2dd\uc758 \ub450 \ubc88\uc9f8 \ud56d\uc740 <em>\uc778\ucd9c \ud398\ub110\ud2f0<\/em> \ub85c \uc54c\ub824\uc838 \uc788\uc2b5\ub2c8\ub2e4. \ub2a5\uc120 \ud68c\uadc0 \ubd84\uc11d\uc5d0\uc11c\ub294 \uac00\ub2a5\ud55c \uac00\uc7a5 \ub0ae\uc740 MSE \ud14c\uc2a4\ud2b8(\ud3c9\uade0 \uc81c\uacf1 \uc624\ucc28)\ub97c \uc0dd\uc131\ud558\ub294 \u03bb \uac12\uc744 \uc120\ud0dd\ud569\ub2c8\ub2e4.<\/span><\/p>\n<p> <span style=\"color: #000000;\">\uc774 \ud29c\ud1a0\ub9ac\uc5bc\uc5d0\uc11c\ub294 R\uc5d0\uc11c \ub2a5\uc120 \ud68c\uadc0\ub97c \uc218\ud589\ud558\ub294 \ubc29\ubc95\uc5d0 \ub300\ud55c \ub2e8\uacc4\ubcc4 \uc608\ub97c \uc81c\uacf5\ud569\ub2c8\ub2e4.<\/span><\/p>\n<h3> <span style=\"color: #000000;\"><strong>1\ub2e8\uacc4: \ub370\uc774\ud130 \ub85c\ub4dc<\/strong><\/span><\/h3>\n<p> <span style=\"color: #000000;\">\uc774 \uc608\uc5d0\uc11c\ub294 <strong>mtcars<\/strong> \ub77c\ub294 R\uc758 \ub0b4\uc7a5 \ub370\uc774\ud130 \uc138\ud2b8\ub97c \uc0ac\uc6a9\ud569\ub2c8\ub2e4. <strong>hp\ub97c<\/strong> \ubc18\uc751 \ubcc0\uc218\ub85c \uc0ac\uc6a9\ud558\uace0 \ub2e4\uc74c \ubcc0\uc218\ub97c \uc608\uce21 \ubcc0\uc218\ub85c \uc0ac\uc6a9\ud569\ub2c8\ub2e4.<\/span><\/p>\n<ul>\n<li> <span style=\"color: #000000;\">mpg<\/span><\/li>\n<li> <span style=\"color: #000000;\">\ubb34\uac8c<\/span><\/li>\n<li> <span style=\"color: #000000;\">\ub625<\/span><\/li>\n<li> <span style=\"color: #000000;\">q\ucd08<\/span><\/li>\n<\/ul>\n<p> <span style=\"color: #000000;\">\ub2a5\uc120 \ud68c\uadc0\ub97c \uc218\ud589\ud558\uae30 \uc704\ud574 <strong>glmnet<\/strong> \ud328\ud0a4\uc9c0\uc758 \uae30\ub2a5\uc744 \uc0ac\uc6a9\ud569\ub2c8\ub2e4. \uc774 \ud328\ud0a4\uc9c0\uc5d0\uc11c\ub294 <a href=\"https:\/\/statorials.org\/ko\/\u1107\u1167\u11ab\u1109\u116e-\u1109\u1165\u11af\u1106\u1167\u11bc-\u110b\u1173\u11bc\u1103\u1161\u11b8\/\" target=\"_blank\" rel=\"noopener noreferrer\">\uc751\ub2f5 \ubcc0\uc218\uac00<\/a> \ubca1\ud130\uc5ec\uc57c \ud558\uace0 \uc608\uce21 \ubcc0\uc218 \uc138\ud2b8\uac00 <strong>data.matrix<\/strong> \ud074\ub798\uc2a4\uc5d0 \uc18d\ud574\uc57c \ud569\ub2c8\ub2e4.<\/span><\/p>\n<p> <span style=\"color: #000000;\">\ub2e4\uc74c \ucf54\ub4dc\ub294 \ub370\uc774\ud130\ub97c \uc815\uc758\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;\">#define response variable<\/span>\ny &lt;- mtcars$hp\n\n<span style=\"color: #008080;\">#define matrix of predictor variables\n<\/span>x &lt;- data.matrix(mtcars[, c('mpg', 'wt', 'drat', 'qsec')])\n<\/strong><\/span><\/pre>\n<h3> <span style=\"color: #000000;\"><strong>2\ub2e8\uacc4: \ub2a5\ud615 \ud68c\uadc0 \ubaa8\ub378 \uc801\ud569<\/strong><\/span><\/h3>\n<p> <span style=\"color: #000000;\">\ub2e4\uc74c\uc73c\ub85c <strong>glmnet()<\/strong> \ud568\uc218\ub97c \uc0ac\uc6a9\ud558\uc5ec Ridge \ud68c\uadc0 \ubaa8\ub378\uc744 \ub9de\ucd94\uace0 <strong>alpha=0<\/strong> \uc744 \uc9c0\uc815\ud569\ub2c8\ub2e4.<\/span><\/p>\n<p> <span style=\"color: #000000;\">\uc54c\ud30c\ub97c 1\ub85c \uc124\uc815\ud558\ub294 \uac83\uc740 \uc62c\uac00\ubbf8 \ud68c\uadc0\ub97c \uc0ac\uc6a9\ud558\ub294 \uac83\uacfc \ub3d9\uc77c\ud558\uba70, \uc54c\ud30c\ub97c 0\uacfc 1 \uc0ac\uc774\uc758 \uac12\uc73c\ub85c \uc124\uc815\ud558\ub294 \uac83\uc740 \ud0c4\uc131\ub9dd\uc744 \uc0ac\uc6a9\ud558\ub294 \uac83\uacfc \ub3d9\uc77c\ud569\ub2c8\ub2e4.<\/span><\/p>\n<p> <span style=\"color: #000000;\">\ub610\ud55c \ub2a5\ud615 \ud68c\uadc0 \ubd84\uc11d\uc5d0\uc11c\ub294 \uac01 \uc608\uce21 \ubcc0\uc218\uc758 \ud3c9\uade0\uc774 0\uc774\uace0 \ud45c\uc900 \ud3b8\ucc28\uac00 1\uc774 \ub418\ub3c4\ub85d \ub370\uc774\ud130\ub97c \ud45c\uc900\ud654\ud574\uc57c \ud569\ub2c8\ub2e4.<\/span><\/p>\n<p> <span style=\"color: #000000;\">\ub2e4\ud589\ud788 <strong>glmnet()\uc740<\/strong> \uc790\ub3d9\uc73c\ub85c \uc774 \ud45c\uc900\ud654\ub97c \uc218\ud589\ud569\ub2c8\ub2e4. \ubcc0\uc218\ub97c \uc774\ubbf8 \ud45c\uc900\ud654\ud55c \uacbd\uc6b0\uc5d0\ub294 <strong>standardize=False\ub97c<\/strong> \uc9c0\uc815\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4.<\/span><\/p>\n<pre style=\"background-color: #ececec; font-size: 15px;\"> <span style=\"color: #000000;\"><strong><span style=\"color: #008080;\"><span style=\"color: #000000;\"><span style=\"color: #993300;\">library<\/span> (glmnet)<\/span>\n\n#fit ridge regression model\n<\/span>model &lt;- glmnet(x, y, alpha = <span style=\"color: #008000;\">0<\/span> )\n\n<span style=\"color: #008080;\">#view summary of model\n<\/span>summary(model)\n\n          Length Class Mode   \na0 100 -none- numeric\nbeta 400 dgCMatrix S4     \ndf 100 -none- numeric\ndim 2 -none- numeric\nlambda 100 -none- numeric\ndev.ratio 100 -none- numeric\nnulldev 1 -none- numeric\nnpasses 1 -none- numeric\njerr 1 -none- numeric\noffset 1 -none- logical\ncall 4 -none- call   \nnobs 1 -none- numeric\n<\/strong><\/span><\/pre>\n<h3> <span style=\"color: #000000;\"><strong>3\ub2e8\uacc4: Lambda\uc5d0 \ub300\ud55c \ucd5c\uc801 \uac12 \uc120\ud0dd<\/strong><\/span><\/h3>\n<p> <span style=\"color: #000000;\">\ub2e4\uc74c\uc73c\ub85c <a href=\"https:\/\/statorials.org\/ko\/k-\u1100\u1167\u11b8-\u1100\u116d\u110e\u1161-\u1100\u1165\u11b7\u110c\u1173\u11bc\/\" target=\"_blank\" rel=\"noopener noreferrer\">k-\uacb9 \uad50\ucc28 \uac80\uc99d\uc744<\/a> \uc0ac\uc6a9\ud558\uc5ec \uac00\uc7a5 \ub0ae\uc740 \ud14c\uc2a4\ud2b8 \ud3c9\uade0 \uc81c\uacf1 \uc624\ucc28(MSE)\ub97c \uc0dd\uc131\ud558\ub294 \ub78c\ub2e4 \uac12\uc744 \uc2dd\ubcc4\ud569\ub2c8\ub2e4.<\/span><\/p>\n<p> <span style=\"color: #000000;\">\ub2e4\ud589\ud788 <strong>glmnet\uc5d0\ub294<\/strong> k = 10\ubc88\uc744 \uc0ac\uc6a9\ud558\uc5ec k-\uacb9 \uad50\ucc28 \uac80\uc99d\uc744 \uc790\ub3d9\uc73c\ub85c \uc218\ud589\ud558\ub294 <strong>cv.glmnet()<\/strong> \ud568\uc218\uac00 \uc788\uc2b5\ub2c8\ub2e4.<\/span> <\/p>\n<pre style=\"background-color: #ececec; font-size: 15px;\"> <span style=\"color: #000000;\"><strong><span style=\"color: #008080;\">#perform k-fold cross-validation to find optimal lambda value\n<\/span>cv_model &lt;- cv. <span style=\"color: #3366ff;\">glmnet<\/span> (x, y, alpha = <span style=\"color: #008000;\">0<\/span> )\n\n<span style=\"color: #008080;\">#find optimal lambda value that minimizes test MSE\n<\/span>best_lambda &lt;- cv_model$ <span style=\"color: #3366ff;\">lambda<\/span> . <span style=\"color: #3366ff;\">min<\/span>\nbest_lambda\n\n[1] 10.04567\n\n<span style=\"color: #008080;\">#produce plot of test MSE by lambda value<\/span>\nplot(cv_model) \n<\/strong><\/span><\/pre>\n<p><img decoding=\"async\" loading=\"lazy\" class=\"aligncenter wp-image-11860 \" src=\"https:\/\/statorials.org\/wp-content\/uploads\/2023\/08\/faiter1.png\" alt=\"R\uc758 \ub2a5\uc120 \ud68c\uadc0\uc5d0 \ub300\ud55c \uad50\ucc28 \uac80\uc99d\" width=\"443\" height=\"426\" srcset=\"\" sizes=\"auto, \"><\/p>\n<p> <span style=\"color: #000000;\">MSE \ud14c\uc2a4\ud2b8\ub97c \ucd5c\uc18c\ud654\ud558\ub294 \ub78c\ub2e4 \uac12\uc740 <strong>10.04567<\/strong> \uc785\ub2c8\ub2e4.<\/span><\/p>\n<h3> <span style=\"color: #000000;\"><strong>4\ub2e8\uacc4: \ucd5c\uc885 \ubaa8\ub378 \ubd84\uc11d<\/strong><\/span><\/h3>\n<p> <span style=\"color: #000000;\">\ub9c8\uc9c0\ub9c9\uc73c\ub85c \ucd5c\uc801\uc758 \ub78c\ub2e4 \uac12\uc744 \ud1b5\ud574 \uc0dd\uc131\ub41c \ucd5c\uc885 \ubaa8\ub378\uc744 \ubd84\uc11d\ud560 \uc218 \uc788\ub2e4.<\/span><\/p>\n<p> <span style=\"color: #000000;\">\ub2e4\uc74c \ucf54\ub4dc\ub97c \uc0ac\uc6a9\ud558\uc5ec \uc774 \ubaa8\ub378\uc5d0 \ub300\ud55c \uacc4\uc218 \ucd94\uc815\uce58\ub97c \uc5bb\uc744 \uc218 \uc788\uc2b5\ub2c8\ub2e4.<\/span><\/p>\n<pre style=\"background-color: #ececec; font-size: 15px;\"> <span style=\"color: #000000;\"><strong><span style=\"color: #008080;\">#find coefficients of best model\n<\/span>best_model &lt;- glmnet(x, y, alpha = <span style=\"color: #008000;\">0<\/span> , lambda = best_lambda)\ncoef(best_model)\n\n5 x 1 sparse Matrix of class \"dgCMatrix\"\n                    s0\n(Intercept) 475.242646\nmpg -3.299732\nwt 19.431238\ndrat -1.222429\nqsec -17.949721<\/strong><\/span><\/pre>\n<p> <span style=\"color: #000000;\">\ub610\ud55c \ub78c\ub2e4 \uc99d\uac00\ub85c \uc778\ud574 \uacc4\uc218 \ucd94\uc815\uac12\uc774 \uc5b4\ub5bb\uac8c \ubcc0\uacbd\ub418\uc5c8\ub294\uc9c0 \uc2dc\uac01\ud654\ud558\uae30 \uc704\ud574 \ucd94\uc801 \ud50c\ub86f\uc744 \uc0dd\uc131\ud560 \uc218\ub3c4 \uc788\uc2b5\ub2c8\ub2e4.<\/span> <\/p>\n<pre style=\"background-color: #ececec; font-size: 15px;\"> <span style=\"color: #000000;\"><strong><span style=\"color: #008080;\">#produce Ridge trace plot<\/span>\nplot(model, xvar = \" <span style=\"color: #008000;\">lambda<\/span> \")<\/strong><\/span> <\/pre>\n<p><img decoding=\"async\" loading=\"lazy\" class=\"aligncenter wp-image-11861 \" src=\"https:\/\/statorials.org\/wp-content\/uploads\/2023\/08\/creter2.png\" alt=\"R\uc758 \ub2a5\uc120 \ucd94\uc801\" width=\"419\" height=\"411\" srcset=\"\" sizes=\"auto, \"><\/p>\n<p> <span style=\"color: #000000;\">\ub9c8\uc9c0\ub9c9\uc73c\ub85c \ud6c8\ub828 \ub370\uc774\ud130\uc5d0 \ub300\ud55c <a href=\"https:\/\/statorials.org\/ko\/\u110c\u1169\u11c2\u110b\u1173\u11ab-r-\u110c\u1166\u1100\u1169\u11b8-\u1100\u1161\u11b9\/\" target=\"_blank\" rel=\"noopener noreferrer\">\ubaa8\ub378\uc758 R-\uc81c\uacf1\uc744<\/a> \uacc4\uc0b0\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4.<\/span><\/p>\n<pre style=\"background-color: #ececec; font-size: 15px;\"> <span style=\"color: #000000;\"><strong><span style=\"color: #008080;\">#use fitted best model to make predictions\n<\/span>y_predicted &lt;- <span style=\"color: #3366ff;\">predict<\/span> (model, s = best_lambda, newx = x)\n\n<span style=\"color: #008080;\">#find OHS and SSE<\/span>\nsst &lt;- <span style=\"color: #3366ff;\">sum<\/span> ((y - <span style=\"color: #3366ff;\">mean<\/span> (y))^2)\nsse &lt;- <span style=\"color: #3366ff;\">sum<\/span> ((y_predicted - y)^2)\n\n<span style=\"color: #008080;\">#find R-Squared\n<\/span>rsq &lt;- 1 - sse\/sst\nrsq\n\n[1] 0.7999513\n<\/strong><\/span><\/pre>\n<p> <span style=\"color: #000000;\">R \uc81c\uacf1\uc740 <strong>0.7999513<\/strong> \uc785\ub2c8\ub2e4. \uc989, \uac00\uc7a5 \uc88b\uc740 \ubaa8\ub378\uc740 \ud6c8\ub828 \ub370\uc774\ud130\uc758 \ubc18\uc751\uac12 \ubcc0\ud654\ub97c <strong>79.99%<\/strong> \uc124\uba85\ud560 \uc218 \uc788\uc5c8\ub2e4.<\/span><\/p>\n<p> <span style=\"color: #000000;\">\uc774 \uc608\uc81c\uc5d0 \uc0ac\uc6a9\ub41c \uc804\uccb4 R \ucf54\ub4dc\ub294 <a href=\"https:\/\/github.com\/Statorials\/R-Guides\/blob\/main\/ridge_regression.R\" target=\"_blank\" rel=\"noopener noreferrer\">\uc5ec\uae30\uc5d0\uc11c<\/a> \ucc3e\uc744 \uc218 \uc788\uc2b5\ub2c8\ub2e4.<\/span><\/p>\n","protected":false},"excerpt":{"rendered":"<p>\ub2a5\ud615 \ud68c\uadc0\ub294 \ub370\uc774\ud130\uc5d0 \ub2e4\uc911 \uacf5\uc120\uc131\uc774 \uc874\uc7ac\ud560 \ub54c \ud68c\uadc0 \ubaa8\ub378\uc744 \uc801\ud569\uc2dc\ud0a4\ub294 \ub370 \uc0ac\uc6a9\ud560 \uc218 \uc788\ub294 \ubc29\ubc95\uc785\ub2c8\ub2e4. \uac04\ub2e8\ud788 \ub9d0\ud574\uc11c, \ucd5c\uc18c \uc81c\uacf1 \ud68c\uadc0\ub294 \uc794\ucc28 \uc81c\uacf1\ud569(RSS)\uc744 \ucd5c\uc18c\ud654\ud558\ub294 \uacc4\uc218 \ucd94\uc815\uac12\uc744 \ucc3e\uc73c\ub824\uace0 \uc2dc\ub3c4\ud569\ub2c8\ub2e4. RSS = \u03a3(y i \u2013 \u0177 i )2 \uae08: \u03a3 : \ud569\uacc4\ub97c \uc758\ubbf8\ud558\ub294 \uadf8\ub9ac\uc2a4 \uae30\ud638 y i : i\ubc88\uc9f8 \uad00\uce21\uac12\uc5d0 \ub300\ud55c \uc2e4\uc81c \uc751\ub2f5 \uac12 \u0177 i : \ub2e4\uc911\uc120\ud615\ud68c\uadc0\ubaa8\ub378\uc744 [&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-1192","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\uc758 \ub2a5\uc120 \ud68c\uadc0(\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 \ub2a5\uc120 \ud68c\uadc0\ub97c 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