{"id":3118,"date":"2023-07-19T03:05:15","date_gmt":"2023-07-19T03:05:15","guid":{"rendered":"https:\/\/statorials.org\/ko\/sklearn-%e1%84%87%e1%85%ae%e1%86%ab%e1%84%85%e1%85%b2-%e1%84%87%e1%85%a9%e1%84%80%e1%85%a9%e1%84%89%e1%85%a5\/"},"modified":"2023-07-19T03:05:15","modified_gmt":"2023-07-19T03:05:15","slug":"sklearn-%e1%84%87%e1%85%ae%e1%86%ab%e1%84%85%e1%85%b2-%e1%84%87%e1%85%a9%e1%84%80%e1%85%a9%e1%84%89%e1%85%a5","status":"publish","type":"post","link":"https:\/\/statorials.org\/ko\/sklearn-%e1%84%87%e1%85%ae%e1%86%ab%e1%84%85%e1%85%b2-%e1%84%87%e1%85%a9%e1%84%80%e1%85%a9%e1%84%89%e1%85%a5\/","title":{"rendered":"Sklearn\uc5d0\uc11c \ubd84\ub958 \ubcf4\uace0\uc11c\ub97c \ud574\uc11d\ud558\ub294 \ubc29\ubc95(\uc608\uc81c \ud3ec\ud568)"},"content":{"rendered":"<p><\/p>\n<hr>\n<p><span style=\"color: #000000;\">\uae30\uacc4 \ud559\uc2b5\uc5d0\uc11c <a href=\"https:\/\/statorials.org\/ko\/\u1112\u116c\u1100\u1171-\u1103\u1162-\u1107\u116e\u11ab\u1105\u1172\/\" target=\"_blank\" rel=\"noopener\">\ubd84\ub958 \ubaa8\ub378\uc744<\/a> \uc0ac\uc6a9\ud560 \ub54c \uc138 \uac00\uc9c0 \uacf5\ud1b5 \uce21\uc815\ud56d\ubaa9\uc744 \uc0ac\uc6a9\ud558\uc5ec \ubaa8\ub378 \ud488\uc9c8\uc744 \ud3c9\uac00\ud569\ub2c8\ub2e4.<\/span><\/p>\n<p> <span style=\"color: #000000;\"><strong>1. \uc815\ud655\ub3c4<\/strong> : \uc804\uccb4 \uae0d\uc815\uc801 \uc608\uce21 \ub300\ube44 \uc62c\ubc14\ub978 \uae0d\uc815\uc801 \uc608\uce21\uc758 \ube44\uc728\uc785\ub2c8\ub2e4.<\/span><\/p>\n<p> <span style=\"color: #000000;\"><strong>2. \uc7ac\ud604\uc728(Recall)<\/strong> : \uc804\uccb4 \uc2e4\uc81c \uae0d\uc815 \ub300\ube44 \uc62c\ubc14\ub978 \uae0d\uc815 \uc608\uce21\uc758 \ube44\uc728\uc785\ub2c8\ub2e4.<\/span><\/p>\n<p> <span style=\"color: #000000;\"><strong>3. F1 \uc810\uc218<\/strong> : \uc815\ubc00\ub3c4\uc640 \uc7ac\ud604\uc728\uc758 \uac00\uc911 \uc870\ud654 \ud3c9\uade0\uc785\ub2c8\ub2e4. \ubaa8\ub378\uc774 1\uc5d0 \uac00\uae4c\uc6b8\uc218\ub85d \ub354 \uc88b\uc740 \ubaa8\ub378\uc785\ub2c8\ub2e4.<\/span><\/p>\n<ul>\n<li> <span style=\"color: #000000;\">F1 \uc810\uc218: 2* (\uc815\ubc00\ub3c4 * \uc7ac\ud604\uc728) \/ (\uc815\ubc00\ub3c4 + \uc7ac\ud604\uc728)<\/span><\/li>\n<\/ul>\n<p> <span style=\"color: #000000;\"><span style=\"color: #000000;\">\uc774 \uc138 \uac00\uc9c0 \uc9c0\ud45c\ub97c \uc0ac\uc6a9\ud558\uba74 \ud2b9\uc815 \ubd84\ub958 \ubaa8\ub378\uc774 \ud2b9\uc815 <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\">\uc751\ub2f5 \ubcc0\uc218<\/a> \uc5d0 \ub300\ud55c \uacb0\uacfc\ub97c \uc5bc\ub9c8\ub098 \uc798 \uc608\uce21\ud560 \uc218 \uc788\ub294\uc9c0 \uc774\ud574\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4.<\/span><\/span><\/p>\n<p> <span style=\"color: #000000;\">\ub2e4\ud589\ud788 Python\uc5d0\uc11c \ubd84\ub958 \ubaa8\ub378\uc744 \ud53c\ud305\ud560 \ub54c <strong>sklearn<\/strong> \ub77c\uc774\ube0c\ub7ec\ub9ac\uc758 <strong>classification_report()<\/strong> \ud568\uc218\ub97c \uc0ac\uc6a9\ud558\uc5ec \uc774\ub7ec\ud55c \uc138 \uac00\uc9c0 \uce21\uc815\ud56d\ubaa9\uc744 \uc0dd\uc131\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4.<\/span><\/p>\n<p> <span style=\"color: #000000;\">\ub2e4\uc74c \uc608\uc5d0\uc11c\ub294 \uc774 \uae30\ub2a5\uc744 \uc2e4\uc81c\ub85c \uc0ac\uc6a9\ud558\ub294 \ubc29\ubc95\uc744 \ubcf4\uc5ec\uc90d\ub2c8\ub2e4.<\/span><\/p>\n<h3> <span style=\"color: #000000;\"><strong>\uc608: sklearn\uc5d0\uc11c \ubd84\ub958 \ubcf4\uace0\uc11c\ub97c \uc0ac\uc6a9\ud558\ub294 \ubc29\ubc95<\/strong><\/span><\/h3>\n<p> <span style=\"color: #000000;\">\uc774 \uc608\uc5d0\uc11c\ub294 \ud3ec\uc778\ud2b8\uc640 \uc5b4\uc2dc\uc2a4\ud2b8\ub97c \uc0ac\uc6a9\ud558\uc5ec 1,000\uba85\uc758 \ub300\ud559 \ub18d\uad6c \uc120\uc218\uac00 NBA\uc5d0 \ub4dc\ub798\ud504\ud2b8\ub420\uc9c0 \uc5ec\ubd80\ub97c \uc608\uce21\ud558\ub294 \ub85c\uc9c0\uc2a4\ud2f1 \ud68c\uadc0 \ubaa8\ub378\uc744 \uc801\uc6a9\ud569\ub2c8\ub2e4.<\/span><\/p>\n<p> <span style=\"color: #000000;\">\uba3c\uc800 Python\uc5d0\uc11c \ub85c\uc9c0\uc2a4\ud2f1 \ud68c\uadc0\ub97c \uc218\ud589\ud558\ub294 \ub370 \ud544\uc694\ud55c \ud328\ud0a4\uc9c0\ub97c \uac00\uc838\uc635\ub2c8\ub2e4.<\/span><\/p>\n<pre style=\"background-color: #ececec; font-size: 15px;\"> <strong><span style=\"color: #008000;\">import<\/span> pandas <span style=\"color: #008000;\">as<\/span> pd\n<span style=\"color: #008000;\">import<\/span> numpy <span style=\"color: #008000;\">as<\/span> np\n<span style=\"color: #008000;\">from<\/span> sklearn. <span style=\"color: #3366ff;\">model_selection<\/span> <span style=\"color: #008000;\">import<\/span> train_test_split\n<span style=\"color: #008000;\">from<\/span> sklearn. <span style=\"color: #3366ff;\">linear_model<\/span> <span style=\"color: #008000;\">import<\/span> LogisticRegression\n<span style=\"color: #008000;\">from<\/span> sklearn. <span style=\"color: #3366ff;\">metrics<\/span> <span style=\"color: #008000;\">import<\/span> classification_report<\/strong>\n<\/pre>\n<p> <span style=\"color: #000000;\">\ub2e4\uc74c\uc73c\ub85c, 1000\uba85\uc758 \ub18d\uad6c \uc120\uc218 \uc815\ubcf4\ub97c \ud3ec\ud568\ud558\ub294 \ub370\uc774\ud130 \ud504\ub808\uc784\uc744 \uc0dd\uc131\ud558\uaca0\uc2b5\ub2c8\ub2e4.<\/span><\/p>\n<pre style=\"background-color: #ececec; font-size: 15px;\"> <span style=\"color: #000000;\"><strong><span style=\"color: #008080;\">#make this example reproducible\n<\/span>n.p. <span style=\"color: #3366ff;\">random<\/span> . <span style=\"color: #3366ff;\">seeds<\/span> (1)\n\n<span style=\"color: #008080;\">#createDataFrame\n<\/span>df = pd. <span style=\"color: #3366ff;\">DataFrame<\/span> ({' <span style=\"color: #ff0000;\">points<\/span> ': np. <span style=\"color: #3366ff;\">random<\/span> . <span style=\"color: #3366ff;\">randint<\/span> (30, size=1000),\n                   ' <span style=\"color: #ff0000;\">assists<\/span> ': np. <span style=\"color: #3366ff;\">random<\/span> . <span style=\"color: #3366ff;\">randint<\/span> (12, size=1000),\n                   ' <span style=\"color: #ff0000;\">drafted<\/span> ': np. <span style=\"color: #3366ff;\">random<\/span> . <span style=\"color: #3366ff;\">randint<\/span> (2, size=1000)})\n\n<span style=\"color: #008080;\">#view DataFrame\n<\/span>df. <span style=\"color: #3366ff;\">head<\/span> ()\n\n\tpoints assists drafted\n0 5 1 1\n1 11 8 0\n2 12 4 1\n3 8 7 0\n4 9 0 0\n<\/strong><\/span><\/pre>\n<p> <span style=\"color: #000000;\"><strong>\ucc38\uace0<\/strong> : \uac12\uc774 <strong>0<\/strong> \uc774\uba74 \uc120\uc218\uac00 \ub4dc\ub798\ud504\ud2b8\ub418\uc9c0 \uc54a\uc558\uc74c\uc744 \ub098\ud0c0\ub0b4\uace0 \uac12\uc774 <strong>1<\/strong> \uc774\uba74 \uc120\uc218\uac00 \ub4dc\ub798\ud504\ud2b8\ub418\uc5c8\uc74c\uc744 \ub098\ud0c0\ub0c5\ub2c8\ub2e4.<\/span><\/p>\n<p> <span style=\"color: #000000;\">\ub2e4\uc74c\uc73c\ub85c \ub370\uc774\ud130\ub97c \ud6c8\ub828 \uc138\ud2b8\uc640 \ud14c\uc2a4\ud2b8 \uc138\ud2b8\ub85c \ubd84\ud560\ud558\uace0 \ub85c\uc9c0\uc2a4\ud2f1 \ud68c\uadc0 \ubaa8\ub378\uc744 \ud53c\ud305\ud569\ub2c8\ub2e4.<\/span><\/p>\n<pre style=\"background-color: #ececec; font-size: 15px;\"> <strong><span style=\"color: #008080;\">#define the predictor variables and the response variable\n<\/span>X = df[[' <span style=\"color: #ff0000;\">points<\/span> ', ' <span style=\"color: #ff0000;\">assists<\/span> ']]\ny = df[' <span style=\"color: #ff0000;\">drafted<\/span> ']\n\n<span style=\"color: #008080;\">#split the dataset into training (70%) and testing (30%) sets\n<\/span>X_train,X_test,y_train,y_test = <span style=\"color: #3366ff;\">train_test_split<\/span> (X,y,test_size=0.3,random_state=0)  \n\n<\/strong><strong><span style=\"color: #008080;\">#instantiate the model\n<\/span>logistic_regression = LogisticRegression()\n\n<span style=\"color: #008080;\">#fit the model using the training data\n<\/span>logistic_regression. <span style=\"color: #3366ff;\">fit<\/span> (X_train,y_train)\n\n<span style=\"color: #008080;\">#use model to make predictions on test data\n<\/span>y_pred = logistic_regression. <span style=\"color: #3366ff;\">predict<\/span> (X_test)<\/strong><\/pre>\n<p> <span style=\"color: #000000;\">\ub9c8\uc9c0\ub9c9\uc73c\ub85c <strong>classification_report()<\/strong> \ud568\uc218\ub97c \uc0ac\uc6a9\ud558\uc5ec \ubaa8\ub378\uc758 \ubd84\ub958 \uce21\uc815\ud56d\ubaa9\uc744 \uc778\uc1c4\ud569\ub2c8\ub2e4.<\/span><\/p>\n<pre style=\"background-color: #ececec; font-size: 15px;\"> <strong><span style=\"color: #008080;\">#print classification report for model\n<span style=\"color: #000000;\"><span style=\"color: #008000;\">print<\/span> (classification_report(y_test, y_pred))\n\n              precision recall f1-score support\n\n           0 0.51 0.58 0.54 160\n           1 0.43 0.36 0.40 140\n\n    accuracy 0.48 300\n   macro avg 0.47 0.47 0.47 300\nweighted avg 0.47 0.48 0.47 300\n<\/span><\/span><\/strong><\/pre>\n<p> <span style=\"color: #000000;\">\uacb0\uacfc\ub97c \ud574\uc11d\ud558\ub294 \ubc29\ubc95\uc740 \ub2e4\uc74c\uacfc \uac19\uc2b5\ub2c8\ub2e4.<\/span><\/p>\n<p> <span style=\"color: #000000;\"><strong>\uc124\uba85<\/strong> : \ubaa8\ub378\uc5d0\uc11c \uc790\uc2e0\uc774 \ub4dc\ub798\ud504\ud2b8\ub420 \uac83\uc774\ub77c\uace0 \uc608\uce21\ud55c \ubaa8\ub4e0 \uc120\uc218 \uc911 \uc2e4\uc81c\ub85c\ub294 <strong>43%<\/strong> \ub9cc\uc774 \ub4dc\ub798\ud504\ud2b8\ub418\uc5c8\uc2b5\ub2c8\ub2e4.<\/span><\/p>\n<p> <span style=\"color: #000000;\"><strong>\uc54c\ub9bc<\/strong> : \uc2e4\uc81c\ub85c \ub4dc\ub798\ud504\ud2b8\ub41c \ubaa8\ub4e0 \uc120\uc218 \uc911\uc5d0\uc11c \ubaa8\ub378\uc740 \uadf8 \uc911 <strong>36%<\/strong> \uc5d0 \ub300\ud574\uc11c\ub9cc \uc774 \uacb0\uacfc\ub97c \uc815\ud655\ud558\uac8c \uc608\uce21\ud588\uc2b5\ub2c8\ub2e4.<\/span><\/p>\n<p> <span style=\"color: #000000;\"><strong>F1 \uc810\uc218<\/strong> : \uc774 \uac12\uc740 \ub2e4\uc74c\uacfc \uac19\uc774 \uacc4\uc0b0\ub429\ub2c8\ub2e4.<\/span><\/p>\n<ul>\n<li> <span style=\"color: #000000;\">F1 \uc810\uc218: 2* (\uc815\ubc00\ub3c4 * \uc7ac\ud604\uc728) \/ (\uc815\ubc00\ub3c4 + \uc7ac\ud604\uc728)<\/span><\/li>\n<li> <span style=\"color: #000000;\">F1 \uc810\uc218: 2*(.43*.36)\/(.43+.36)<\/span><\/li>\n<li> <span style=\"color: #000000;\">F1 \ub4f1\uae09: <strong>0.40<\/strong> .<\/span><\/li>\n<\/ul>\n<p> <span style=\"color: #000000;\">\uc774 \uac12\uc740 1\uc5d0 \ub9e4\uc6b0 \uac00\uae5d\uc9c0 \uc54a\uae30 \ub54c\ubb38\uc5d0 \ubaa8\ub378\uc774 \uc120\uc218\uac00 \ub4dc\ub798\ud504\ud2b8\ub420\uc9c0 \uc5ec\ubd80\ub97c \uc81c\ub300\ub85c \uc608\uce21\ud558\uc9c0 \ubabb\ud55c\ub2e4\ub294 \uac83\uc744 \uc54c \uc218 \uc788\uc2b5\ub2c8\ub2e4.<\/span><\/p>\n<p> <span style=\"color: #000000;\"><strong>\uc9c0\uc6d0<\/strong> : \uc774 \uac12\uc740 \ub2e8\uc21c\ud788 \ud14c\uc2a4\ud2b8 \ub370\uc774\ud130 \uc138\ud2b8\uc758 \uac01 \ud074\ub798\uc2a4\uc5d0 \uc18d\ud55c \ud50c\ub808\uc774\uc5b4 \uc218\ub97c \uc54c\ub824\uc90d\ub2c8\ub2e4. \ud14c\uc2a4\ud2b8 \ub370\uc774\ud130 \uc138\ud2b8\uc758 \ud50c\ub808\uc774\uc5b4 \uc911 <strong>160\uba85\uc740<\/strong> \ub4dc\ub798\ud504\ud2b8\ub418\uc9c0 \uc54a\uc558\uace0 <strong>140\uba85\uc740 \ub4dc\ub798\ud504\ud2b8<\/strong> \ub418\uc5c8\uc74c\uc744 \uc54c \uc218 \uc788\uc2b5\ub2c8\ub2e4.<\/span><\/p>\n<p> <span style=\"color: #000000;\"><strong>\ucc38\uace0<\/strong> : <strong>classification_report()<\/strong> \ud568\uc218\uc5d0 \ub300\ud55c \uc804\uccb4 \ubb38\uc11c\ub294 <a href=\"https:\/\/scikit-learn.org\/stable\/modules\/generated\/sklearn.metrics.classification_report.html\" target=\"_blank\" rel=\"noopener\">\uc5ec\uae30\uc5d0\uc11c<\/a> \ucc3e\uc744 \uc218 \uc788\uc2b5\ub2c8\ub2e4.<\/span><\/p>\n<h3> <span style=\"color: #000000;\"><strong>\ucd94\uac00 \ub9ac\uc18c\uc2a4<\/strong><\/span><\/h3>\n<p> <span style=\"color: #000000;\">\ub2e4\uc74c \uc790\uc2b5\uc11c\uc5d0\uc11c\ub294 Python\uc5d0\uc11c \ubd84\ub958 \ubaa8\ub378\uc744 \uc0ac\uc6a9\ud558\ub294 \ubc29\ubc95\uc5d0 \ub300\ud55c \ucd94\uac00 \uc815\ubcf4\ub97c \uc81c\uacf5\ud569\ub2c8\ub2e4.<\/span><\/p>\n<p> <a href=\"https:\/\/statorials.org\/ko\/\u1105\u1169\u110c\u1175\u1109\u1173\u1110\u1175\u11a8-\u1112\u116c\u1100\u1171-\u1111\u1161\u110b\u1175\u110a\u1165\u11ab\/\" target=\"_blank\" rel=\"noopener\">Python\uc5d0\uc11c \ub85c\uc9c0\uc2a4\ud2f1 \ud68c\uadc0\ub97c \uc218\ud589\ud558\ub294 \ubc29\ubc95<\/a><br \/> <a href=\"https:\/\/statorials.org\/ko\/\u1111\u1161\u110b\u1175\u110a\u1165\u11ab-\u1106\u1162\u1110\u1173\u1105\u1175\u11a8\u1109\u1173-\u1112\u1169\u11ab\u1105\u1161\u11ab\/\" target=\"_blank\" rel=\"noopener\">Python\uc5d0\uc11c \ud63c\ub3d9 \ud589\ub82c\uc744 \ub9cc\ub4dc\ub294 \ubc29\ubc95<\/a><br \/> <a href=\"https:\/\/statorials.org\/ko\/\u1100\u1172\u11ab\u1112\u1167\u11bc-\u110c\u1161\u11b8\u1112\u1175\u11ab-\u110c\u1165\u11bc\u1106\u1175\u11af\u1103\u1169-python-sklearn\/\">Python\uc5d0\uc11c \uade0\ud615 \uc7a1\ud78c \uc815\ubc00\ub3c4\ub97c \uacc4\uc0b0\ud558\ub294 \ubc29\ubc95<\/a><\/p>\n","protected":false},"excerpt":{"rendered":"<p>\uae30\uacc4 \ud559\uc2b5\uc5d0\uc11c \ubd84\ub958 \ubaa8\ub378\uc744 \uc0ac\uc6a9\ud560 \ub54c \uc138 \uac00\uc9c0 \uacf5\ud1b5 \uce21\uc815\ud56d\ubaa9\uc744 \uc0ac\uc6a9\ud558\uc5ec \ubaa8\ub378 \ud488\uc9c8\uc744 \ud3c9\uac00\ud569\ub2c8\ub2e4. 1. \uc815\ud655\ub3c4 : \uc804\uccb4 \uae0d\uc815\uc801 \uc608\uce21 \ub300\ube44 \uc62c\ubc14\ub978 \uae0d\uc815\uc801 \uc608\uce21\uc758 \ube44\uc728\uc785\ub2c8\ub2e4. 2. \uc7ac\ud604\uc728(Recall) : \uc804\uccb4 \uc2e4\uc81c \uae0d\uc815 \ub300\ube44 \uc62c\ubc14\ub978 \uae0d\uc815 \uc608\uce21\uc758 \ube44\uc728\uc785\ub2c8\ub2e4. 3. F1 \uc810\uc218 : \uc815\ubc00\ub3c4\uc640 \uc7ac\ud604\uc728\uc758 \uac00\uc911 \uc870\ud654 \ud3c9\uade0\uc785\ub2c8\ub2e4. \ubaa8\ub378\uc774 1\uc5d0 \uac00\uae4c\uc6b8\uc218\ub85d \ub354 \uc88b\uc740 \ubaa8\ub378\uc785\ub2c8\ub2e4. F1 \uc810\uc218: 2* (\uc815\ubc00\ub3c4 [&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-3118","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>sklearn\uc5d0\uc11c \ubd84\ub958 \ubcf4\uace0\uc11c\ub97c \ud574\uc11d\ud558\ub294 \ubc29\ubc95(\uc608\uc81c \ud3ec\ud568) - \ud1b5\uacc4<\/title>\n<meta name=\"description\" content=\"\uc774 \ud29c\ud1a0\ub9ac\uc5bc\uc5d0\uc11c\ub294 Python\uc5d0\uc11c classification_report() \ud568\uc218\ub97c \uc0ac\uc6a9\ud558\ub294 \ubc29\ubc95\uc744 \uc608\uc81c\uc640 \ud568\uaed8 \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\" href=\"https:\/\/statorials.org\/ko\/sklearn-\u1107\u116e\u11ab\u1105\u1172-\u1107\u1169\u1100\u1169\u1109\u1165\/\" \/>\n<meta property=\"og:locale\" content=\"ko_KR\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"sklearn\uc5d0\uc11c \ubd84\ub958 \ubcf4\uace0\uc11c\ub97c \ud574\uc11d\ud558\ub294 \ubc29\ubc95(\uc608\uc81c \ud3ec\ud568) - 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