{"id":40772,"date":"2024-11-04T12:20:22","date_gmt":"2024-11-04T12:20:22","guid":{"rendered":"https:\/\/atmokpo.com\/w\/?p=40772"},"modified":"2024-11-26T06:38:29","modified_gmt":"2024-11-26T06:38:29","slug":"44-%eb%a1%9c%ec%a7%80%ec%8a%a4%ed%8b%b1-%ed%9a%8c%ea%b7%80logistic-regression-%eb%b6%84%eb%a5%98-%eb%ac%b8%ec%a0%9c%ec%97%90%ec%84%9c%ec%9d%98-%eb%a1%9c%ec%a7%80%ec%8a%a4%ed%8b%b1-%ed%9a%8c","status":"publish","type":"post","link":"https:\/\/atmokpo.com\/w\/40772\/","title":{"rendered":"44.\ub85c\uc9c0\uc2a4\ud2f1 \ud68c\uadc0(Logistic Regression), \ubd84\ub958 \ubb38\uc81c\uc5d0\uc11c\uc758 \ub85c\uc9c0\uc2a4\ud2f1 \ud68c\uadc0 \ud65c\uc6a9"},"content":{"rendered":"<h2>\ub85c\uc9c0\uc2a4\ud2f1 \ud68c\uadc0(Logistic Regression)<\/h2>\n<p>\ub85c\uc9c0\uc2a4\ud2f1 \ud68c\uadc0(Logistic Regression)\ub294 \ud1b5\uacc4\ud559 \ubc0f \uae30\uacc4 \ud559\uc2b5 \ubd84\uc57c\uc5d0\uc11c \ub370\uc774\ud130\uc758 \uc774\uc9c4 \ubd84\ub958\ub97c \uc704\ud55c \uae30\ubcf8\uc801\uc774\uace0 \ub110\ub9ac \uc0ac\uc6a9\ub418\ub294 \uae30\ubc95 \uc911 \ud558\ub098\uc785\ub2c8\ub2e4. \uc774 \uc54c\uace0\ub9ac\uc998\uc740 \uc5b4\ub5a4 \uc0ac\uac74\uc758 \ubc1c\uc0dd \ud655\ub960\uc744 \uc608\uce21\ud558\ub294 \ubaa8\ub378\uc744 \ub9cc\ub4dc\ub294 \ub370 \uc0ac\uc6a9\ub418\uba70, \uacb0\uacfc\uac12\uc774 \ub450 \uac00\uc9c0 \ubc94\uc8fc \uc911 \ud558\ub098\ub85c \uc81c\ud55c\ub418\uc5b4 \uc788\ub294 \uc0c1\ud669\uc5d0\uc11c \uc8fc\ub85c \ud65c\uc6a9\ub429\ub2c8\ub2e4. \ubcf8 \uac15\uc88c\uc5d0\uc11c\ub294 \ub85c\uc9c0\uc2a4\ud2f1 \ud68c\uadc0\uc758 \uc6d0\ub9ac, \uc218\ud559\uc801 \ubc30\uacbd, \uc2e4\uc81c \uc0ac\ub840, \uc7a5\ub2e8\uc810\uacfc \ud568\uaed8 \uc774\ub97c \uad6c\ud604\ud558\ub294 \ubc29\ubc95\uc744 \uc790\uc138\ud788 \uc54c\uc544\ubcf4\uaca0\uc2b5\ub2c8\ub2e4.<\/p>\n<h3>1. \ub85c\uc9c0\uc2a4\ud2f1 \ud68c\uadc0\uc758 \uae30\ubcf8 \uac1c\ub150<\/h3>\n<p>\ub85c\uc9c0\uc2a4\ud2f1 \ud68c\uadc0\ub294 \ub3c5\ub9bd \ubcc0\uc218(X)\uc640 \uc885\uc18d \ubcc0\uc218(Y) \uac04\uc758 \uad00\uacc4\ub97c \ubaa8\ub378\ub9c1\ud558\ub294 \ud1b5\uacc4 \ubc29\ubc95\uc785\ub2c8\ub2e4. \uc885\uc18d \ubcc0\uc218\ub294 \uc774\uc9c4\ud615(binary)\uc73c\ub85c, \ub450 \uac00\uc9c0 \ud074\ub798\uc2a4 \uc911 \ud558\ub098(\uc608: \ud569\uaca9\/\ubd88\ud569\uaca9, \uc2a4\ud338\/\ube44\uc2a4\ud338 \ub4f1)\ub85c \uad6c\ubd84\ub429\ub2c8\ub2e4. \ub85c\uc9c0\uc2a4\ud2f1 \ud68c\uadc0\uc758 \ubaa9\ud45c\ub294 \uc8fc\uc5b4\uc9c4 \ub3c5\ub9bd \ubcc0\uc218\ub97c \uae30\ubc18\uc73c\ub85c \ud2b9\uc815 \uc0ac\uac74\uc774 \ubc1c\uc0dd\ud560 \ud655\ub960\uc744 \uacc4\uc0b0\ud558\ub294 \uac83\uc785\ub2c8\ub2e4.<\/p>\n<p>\uc608\ub97c \ub4e4\uc5b4, \uc5b4\ub5a4 \ud559\uc0dd\uc774 \uc218\ud559 \uc2dc\ud5d8\uc5d0 \ud569\uaca9\ud560 \ud655\ub960\uc744 \uc608\uce21\ud558\uace0\uc790 \ud560 \ub54c, \uc774 \ud559\uc0dd\uc758 \uacf5\ubd80 \uc2dc\uac04, \uacfc\uac70 \uc131\uc801 \ub4f1\uc744 \ub3c5\ub9bd \ubcc0\uc218\ub85c \uc0ac\uc6a9\ud558\uace0, \ud569\uaca9\/\ubd88\ud569\uaca9\uc774\ub77c\ub294 \uc774\uc9c4 \uc885\uc18d \ubcc0\uc218\ub97c \uc124\uc815\ud558\uc5ec \ub85c\uc9c0\uc2a4\ud2f1 \ud68c\uadc0 \ubd84\uc11d\uc744 \uc218\ud589\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4.<\/p>\n<h3>2. \ub85c\uc9c0\uc2a4\ud2f1 \ud68c\uadc0\uc758 \uc218\ud559\uc801 \ubc30\uacbd<\/h3>\n<p>\ub85c\uc9c0\uc2a4\ud2f1 \ud68c\uadc0\ub294 \uc120\ud615 \ud68c\uadc0\uc758 \ud655\uc7a5\uc73c\ub85c \ubcfc \uc218 \uc788\uc2b5\ub2c8\ub2e4. \ud558\uc9c0\ub9cc \uc120\ud615 \ud68c\uadc0\uc640\uc758 \uacb0\uc815\uc801\uc778 \ucc28\uc774\ub294 \uc608\uce21\uac12\uc774 \ud655\ub960\uc801\uc774\ub77c\ub294 \uc810\uc785\ub2c8\ub2e4. \uc5b4\ub5a4 \uc0ac\uac74\uc774 \ubc1c\uc0dd\ud560 \ud655\ub960 \\( P(Y=1|X) \\)\ub97c \uc608\uce21\ud558\uae30 \uc704\ud574 \uc2dc\uadf8\ubaa8\uc774\ub4dc \ud568\uc218(sigmoid function)\ub97c \uc0ac\uc6a9\ud569\ub2c8\ub2e4. \uc2dc\uadf8\ubaa8\uc774\ub4dc \ud568\uc218\ub294 \ub2e4\uc74c\uacfc \uac19\uc740 \ud615\ud0dc\ub85c \uc815\uc758\ub429\ub2c8\ub2e4:<\/p>\n<pre>\n\\sigma(z) = \\frac{1}{1 + e^{-z}}\n<\/pre>\n<p>\uc5ec\uae30\uc11c \\( z \\)\ub294 \uc120\ud615 \uc870\ud569\uc73c\ub85c, \\( z = \\beta_0 + \\beta_1X_1 + \\beta_2X_2 + &#8230; + \\beta_nX_n \\) \ub85c \ud45c\ud604\ub429\ub2c8\ub2e4. \\( \\beta_0 \\)\ub294 \uc808\ud3b8(intercept)\uc774\uba70, \\( \\beta_1, \\beta_2, &#8230;, \\beta_n \\)\uc740 \ub3c5\ub9bd \ubcc0\uc218\uc5d0 \ub300\ud55c \ud68c\uadc0 \uacc4\uc218\uc785\ub2c8\ub2e4.<\/p>\n<p>\ud655\ub960 \\( P \\)\ub294 \ub2e4\uc74c\uacfc \uac19\uc774 \ud45c\ud604\ub429\ub2c8\ub2e4:<\/p>\n<pre>\nP(Y=1|X) = \\sigma(\\beta_0 + \\beta_1X_1 + \\beta_2X_2 + ... + \\beta_nX_n)\n<\/pre>\n<p>\uc774\uc81c \uc885\uc18d \ubcc0\uc218 \\( Y \\)\uac00 0\uc77c \ud655\ub960\uc740 1\uc5d0\uc11c \uc704\uc758 \ud655\ub960\uc744 \ube7c\uc11c \uacc4\uc0b0\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4:<\/p>\n<pre>\nP(Y=0|X) = 1 - P(Y=1|X)\n<\/pre>\n<h3>3. \ub85c\uc9c0\uc2a4\ud2f1 \ud68c\uadc0\uc758 \ud559\uc2b5 \ubc29\ubc95<\/h3>\n<p>\ub85c\uc9c0\uc2a4\ud2f1 \ud68c\uadc0 \ubaa8\ub378\uc744 \ud559\uc2b5\ud558\uae30 \uc704\ud574\uc11c\ub294 \uc8fc\uc5b4\uc9c4 \ub370\uc774\ud130\uc5d0\uc11c \ud68c\uadc0 \uacc4\uc218 \\( \\beta \\)\ub97c \ucd94\uc815\ud574\uc57c \ud569\ub2c8\ub2e4. \uc774 \uacfc\uc815\uc740 \ucd5c\ub300 \uc6b0\ub3c4 \ucd94\uc815(Maximum Likelihood Estimation, MLE) \ubc29\ubc95\uc744 \uc0ac\uc6a9\ud558\uc5ec \uc774\ub8e8\uc5b4\uc9d1\ub2c8\ub2e4. \uc6b0\ub3c4 \ud568\uc218(Likelihood Function)\ub294 \uad00\uce21\ub41c \ub370\uc774\ud130\uac00 \uc8fc\uc5b4\uc84c\uc744 \ub54c, \ud30c\ub77c\ubbf8\ud130\uac00 \ud2b9\uc815 \uac12\uc77c \ud655\ub960\uc744 \uc758\ubbf8\ud569\ub2c8\ub2e4. \ub85c\uc9c0\uc2a4\ud2f1 \ud68c\uadc0\uc5d0\uc11c\ub294 \ub2e4\uc74c\uacfc \uac19\uc740 \uc6b0\ub3c4 \ud568\uc218\ub97c \ucde8\ud569\ub2c8\ub2e4:<\/p>\n<pre>\nL(\\beta) = \\prod_{i=1}^{n} P(Y_i|X_i, \\beta) = \\prod_{i=1}^{n} \\left( \\sigma(z_i)^{y_i} (1 - \\sigma(z_i))^{(1 - y_i)} \\right)\n<\/pre>\n<p>\uc5ec\uae30\uc11c \\( y_i \\)\ub294 \uc885\uc18d \ubcc0\uc218\uc758 \uac12\uc774\uba70, \\( n \\)\uc740 \ub370\uc774\ud130 \ud3ec\uc778\ud2b8\uc758 \uc218\uc785\ub2c8\ub2e4. \uc774 \uc6b0\ub3c4 \ud568\uc218\ub97c \ucd5c\ub300\ud654\ud558\uae30 \uc704\ud55c \uacfc\uc815\uc5d0\uc11c \uc8fc\uc5b4\uc9c4 \ub370\uc774\ud130\uc5d0 \ub300\ud55c \ub85c\uadf8 \uc6b0\ub3c4 \ud568\uc218(log-likelihood function)\ub97c \uc138\uc6b0\uace0, \uc774\ub97c \ucd5c\uc801\ud654\ud558\uc5ec \\( \\beta \\)\uc758 \uac12\uc744 \uad6c\ud569\ub2c8\ub2e4.<\/p>\n<h3>4. \ub85c\uc9c0\uc2a4\ud2f1 \ud68c\uadc0\uc758 \ud65c\uc6a9 \uc0ac\ub840<\/h3>\n<p>\ub85c\uc9c0\uc2a4\ud2f1 \ud68c\uadc0\ub294 \uc5ec\ub7ec \ubd84\uc57c\uc5d0\uc11c \ub2e4\uc591\ud55c \ubb38\uc81c \ud574\uacb0\uc5d0 \uc0ac\uc6a9\ub429\ub2c8\ub2e4.<\/p>\n<ul>\n<li><strong>\uc758\ub8cc \ubd84\uc57c:<\/strong> \ud2b9\uc815 \uc9c8\ubcd1\uc5d0 \uac78\ub9b4 \ud655\ub960\uc744 \uc608\uce21\ud558\uae30 \uc704\ud574 \uc0ac\uc6a9\ub429\ub2c8\ub2e4. \uc608\ub97c \ub4e4\uc5b4, \ud761\uc5f0 \uc5ec\ubd80\uc640 \ub098\uc774\ub97c \ub3c5\ub9bd \ubcc0\uc218\ub85c \ub450\uace0 \ud3d0\uc554 \ubc1c\uc0dd \uc5ec\ubd80\ub97c \uc774\uc9c4 \uc885\uc18d \ubcc0\uc218\ub85c \uc124\uc815\ud558\uc5ec \ubaa8\ub378\uc744 \uad6c\ucd95\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4.<\/li>\n<li><strong>\uae08\uc735 \ubd84\uc57c:<\/strong> \ub300\ucd9c \uc2e0\uccad\uc790\uc758 \uc2e0\uc6a9 \uc704\ud5d8\uc744 \ud3c9\uac00\ud558\ub294 \ub370 \ud65c\uc6a9\ub429\ub2c8\ub2e4. \uc774 \uacbd\uc6b0, \ub300\ucd9c \uc2e0\uccad\uc790\uc758 \uc18c\ub4dd, \uc2e0\uc6a9 \uc810\uc218, \uc794\uc561 \ub4f1\uc744 \ub3c5\ub9bd \ubcc0\uc218\ub85c \uc124\uc815\ud558\uace0, \ub300\ucd9c \uc0c1\ud658 \uc5ec\ubd80\ub97c \uc885\uc18d \ubcc0\uc218\ub85c \uc124\uc815\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4.<\/li>\n<li><strong>\ub9c8\ucf00\ud305:<\/strong> \uace0\uac1d\uc758 \uad6c\ub9e4 \uc5ec\ubd80\ub97c \uc608\uce21\ud558\ub294 \ub370 \uc0ac\uc6a9\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4. \uace0\uac1d\uc758 \ub098\uc774, \uc131\ubcc4, \uad6c\ub9e4 \uc774\ub825 \ub4f1\uc744 \ub3c5\ub9bd \ubcc0\uc218\ub85c \ud65c\uc6a9\ud558\uc5ec, \ud2b9\uc815 \uc81c\ud488\uc744 \uad6c\ub9e4\ud560 \ud655\ub960\uc744 \uc608\uce21\ud558\ub294 \ub370 \uc720\uc6a9\ud569\ub2c8\ub2e4.<\/li>\n<\/ul>\n<h3>5. \ub85c\uc9c0\uc2a4\ud2f1 \ud68c\uadc0\uc758 \uc7a5\uc810\uacfc \ub2e8\uc810<\/h3>\n<p><strong>\uc7a5\uc810:<\/strong><\/p>\n<ul>\n<li>\ubaa8\ub378\uc774 \uac04\ub2e8\ud558\uace0 \ud574\uc11d\uc774 \uc26c\uc6b0\uba70, \uc608\uce21 \uacb0\uacfc\ub97c \ud655\ub960\ub85c \uc81c\uacf5\ud558\uc5ec \uc0c1\ud669\uc5d0 \ub300\ud55c \uc774\ud574\ub97c \ub192\uc785\ub2c8\ub2e4.<\/li>\n<li>\ub2e4\uc591\ud55c \ub3c5\ub9bd \ubcc0\uc218\ub97c \uac00\uc9c8 \uc218 \uc788\uc73c\uba70, \ube44\uc120\ud615 \uad00\uacc4\ub97c \uc798 \ucc98\ub9ac\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4.<\/li>\n<li>\uc18d\ub3c4\uac00 \ube60\ub974\uba70, \ub9ce\uc740 \ub370\uc774\ud130\ub97c \ucc98\ub9ac\ud560 \uc218 \uc788\ub294 \uac15\ub825\ud55c \uc131\ub2a5\uc744 \uc790\ub791\ud569\ub2c8\ub2e4.<\/li>\n<\/ul>\n<p><strong>\ub2e8\uc810:<\/strong><\/p>\n<ul>\n<li>\ub3c5\ub9bd \ubcc0\uc218 \uac04\uc758 \uac15\ud55c \uc0c1\uad00\uad00\uacc4(\ub2e4\uc911 \uacf5\uc120\uc131)\uac00 \uc788\uc744 \uacbd\uc6b0 \uc131\ub2a5\uc774 \uc800\ud558\ub420 \uc218 \uc788\uc2b5\ub2c8\ub2e4.<\/li>\n<li>\uc774\uc9c4 \ubd84\ub958 \ubb38\uc81c\uc5d0 \uc801\ud569\ud558\uc9c0\ub9cc, \ub2e4\uc911 \ud074\ub798\uc2a4 \ubb38\uc81c\uc5d0 \ub300\ud574\uc11c\ub294 \uace0\ucc28\uc6d0 \ud68c\uadc0\ub85c\uc758 \ud655\uc7a5\uc774 \ud544\uc694\ud569\ub2c8\ub2e4.<\/li>\n<li>\ubaa8\ub378\uc774 \uc120\ud615\uc801\uc77c \ub54c\uc5d0\ub9cc \uc798 \uc791\ub3d9\ud558\ubbc0\ub85c \ube44\uc120\ud615 \uacb0\uc815 \uacbd\uacc4\uac00 \ud544\uc694\ud55c \uacbd\uc6b0\uc5d0\ub294 \ub2e4\ub978 \ubc29\ubc95\uc744 \uace0\ub824\ud574\uc57c \ud569\ub2c8\ub2e4.<\/li>\n<\/ul>\n<h3>6. \ub85c\uc9c0\uc2a4\ud2f1 \ud68c\uadc0\uc758 \uad6c\ud604<\/h3>\n<p>\ub85c\uc9c0\uc2a4\ud2f1 \ud68c\uadc0\ub294 \ud30c\uc774\uc36c\uc758 \uc5ec\ub7ec \ub77c\uc774\ube0c\ub7ec\ub9ac\uc5d0\uc11c \uc27d\uac8c \uad6c\ud604\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4. \ub300\ud45c\uc801\uc73c\ub85c <strong>scikit-learn<\/strong> \ub77c\uc774\ube0c\ub7ec\ub9ac\ub97c \uc0ac\uc6a9\ud558\uc5ec \ub85c\uc9c0\uc2a4\ud2f1 \ud68c\uadc0 \ubaa8\ub378\uc744 \uad6c\ucd95\ud558\ub294 \uacfc\uc815\uc744 \uc0b4\ud3b4\ubcf4\uaca0\uc2b5\ub2c8\ub2e4.<\/p>\n<pre><code>\nimport numpy as np\nimport pandas as pd\nfrom sklearn.model_selection import train_test_split\nfrom sklearn.linear_model import LogisticRegression\nfrom sklearn.metrics import accuracy_score, confusion_matrix, classification_report\n\n# \ub370\uc774\ud130 \ub85c\ub4dc \ubc0f \uc900\ube44\ndata = pd.read_csv('data.csv')\nX = data[['feature1', 'feature2']]  # \ub3c5\ub9bd \ubcc0\uc218\ny = data['target']  # \uc885\uc18d \ubcc0\uc218\n\n# \ub370\uc774\ud130 \ubd84\ud560\nX_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.2, random_state=42)\n\n# \ub85c\uc9c0\uc2a4\ud2f1 \ud68c\uadc0 \ubaa8\ub378 \ud559\uc2b5\nmodel = LogisticRegression()\nmodel.fit(X_train, y_train)\n\n# \uc608\uce21\ny_pred = model.predict(X_test)\n\n# \uc131\ub2a5 \ud3c9\uac00\naccuracy = accuracy_score(y_test, y_pred)\nconfusion = confusion_matrix(y_test, y_pred)\nreport = classification_report(y_test, y_pred)\n\nprint(f'\uc815\ud655\ub3c4: {accuracy}')\nprint(f'\ud63c\ub3d9 \ud589\ub82c:\\n{confusion}')\nprint(f'\ubd84\ub958 \ub9ac\ud3ec\ud2b8:\\n{report}')\n<\/code><\/pre>\n<p>\uc704\uc758 \ucf54\ub4dc\ub294 \uac04\ub2e8\ud788 \ub85c\uc9c0\uc2a4\ud2f1 \ud68c\uadc0 \ubaa8\ub378\uc744 \uad6c\uc870\ud654\ud55c \uc608\uc2dc\uc785\ub2c8\ub2e4. \ub370\uc774\ud130\ub97c \uc900\ube44\ud558\uace0 \ud6c8\ub828 \ub370\uc774\ud130\uc640 \ud14c\uc2a4\ud2b8 \ub370\uc774\ud130\ub97c \ub098\ub208 \ud6c4, \ub85c\uc9c0\uc2a4\ud2f1 \ud68c\uadc0 \ubaa8\ub378\uc744 \ud559\uc2b5\uc2dc\ud0b5\ub2c8\ub2e4. \ubaa8\ub378\uc774 \ud559\uc2b5\ub41c \ud6c4, \ud14c\uc2a4\ud2b8 \ub370\uc774\ud130\uc5d0 \ub300\ud574 \uc608\uce21\uc744 \uc218\ud589\ud558\uace0 \uadf8 \uc131\ub2a5\uc744 \ud3c9\uac00\ud569\ub2c8\ub2e4.<\/p>\n<h3>7. \uacb0\ub860<\/h3>\n<p>\ub85c\uc9c0\uc2a4\ud2f1 \ud68c\uadc0\ub294 \uc774\uc9c4 \ubd84\ub958 \ubb38\uc81c\ub97c \ud574\uacb0\ud558\uae30 \uc704\ud55c \uac15\ub825\ud55c \ub3c4\uad6c\uc774\uba70, \ud1b5\uacc4\ud559\uc5d0\uc11c\ub294 \ubb3c\ub860 \uae30\uacc4 \ud559\uc2b5\uc5d0\uc11c\ub3c4 \ub2e4\uc591\ud55c \uc751\uc6a9\uc774 \uac00\ub2a5\ud569\ub2c8\ub2e4. \uadf8 \uc720\uc6a9\uc131, \ud574\uc11d\uc758 \uc6a9\uc774\uc131, \uadf8\ub9ac\uace0 \uacc4\uc0b0 \ud6a8\uc728\uc131 \ub355\ubd84\uc5d0 \ub85c\uc9c0\uc2a4\ud2f1 \ud68c\uadc0\ub294 \uc5ec\ub7ec \ubd84\uc57c\uc5d0\uc11c \ub110\ub9ac \uc0ac\uc6a9\ub418\uace0 \uc788\uc2b5\ub2c8\ub2e4. \uadf8\ub7ec\ub098 \ubaa8\ub378\uc774 \uac16\ub294 \ud55c\uacc4\uc640 \uac00\uc815\uc5d0 \uc8fc\uc758\ud558\uba70, \uc0c1\ud669\uc5d0 \ub530\ub77c \uc801\uc808\ud788 \ud65c\uc6a9\ud558\ub294 \uac83\uc774 \uc911\uc694\ud569\ub2c8\ub2e4. \uc55e\uc73c\ub85c\ub3c4 \ub85c\uc9c0\uc2a4\ud2f1 \ud68c\uadc0\ub97c \uae30\ubc18\uc73c\ub85c \ud55c \ub2e4\uc591\ud55c \ubd84\uc11d\uacfc \uadf8 \uc751\uc6a9 \uac00\ub2a5\uc131\uc5d0 \ub300\ud574 \uac80\ud1a0\ud574 \ubcf4\uae30\ub97c \uad8c\uc7a5\ud569\ub2c8\ub2e4.<\/p>\n","protected":false},"excerpt":{"rendered":"<p>\ub85c\uc9c0\uc2a4\ud2f1 \ud68c\uadc0(Logistic Regression) \ub85c\uc9c0\uc2a4\ud2f1 \ud68c\uadc0(Logistic Regression)\ub294 \ud1b5\uacc4\ud559 \ubc0f \uae30\uacc4 \ud559\uc2b5 \ubd84\uc57c\uc5d0\uc11c \ub370\uc774\ud130\uc758 \uc774\uc9c4 \ubd84\ub958\ub97c \uc704\ud55c \uae30\ubcf8\uc801\uc774\uace0 \ub110\ub9ac \uc0ac\uc6a9\ub418\ub294 \uae30\ubc95 \uc911 \ud558\ub098\uc785\ub2c8\ub2e4. \uc774 \uc54c\uace0\ub9ac\uc998\uc740 \uc5b4\ub5a4 \uc0ac\uac74\uc758 \ubc1c\uc0dd \ud655\ub960\uc744 \uc608\uce21\ud558\ub294 \ubaa8\ub378\uc744 \ub9cc\ub4dc\ub294 \ub370 \uc0ac\uc6a9\ub418\uba70, \uacb0\uacfc\uac12\uc774 \ub450 \uac00\uc9c0 \ubc94\uc8fc \uc911 \ud558\ub098\ub85c \uc81c\ud55c\ub418\uc5b4 \uc788\ub294 \uc0c1\ud669\uc5d0\uc11c \uc8fc\ub85c \ud65c\uc6a9\ub429\ub2c8\ub2e4. \ubcf8 \uac15\uc88c\uc5d0\uc11c\ub294 \ub85c\uc9c0\uc2a4\ud2f1 \ud68c\uadc0\uc758 \uc6d0\ub9ac, \uc218\ud559\uc801 \ubc30\uacbd, \uc2e4\uc81c \uc0ac\ub840, \uc7a5\ub2e8\uc810\uacfc \ud568\uaed8 \uc774\ub97c &hellip; <a href=\"https:\/\/atmokpo.com\/w\/40772\/\" class=\"more-link\">\ub354 \ubcf4\uae30<span class=\"screen-reader-text\"> &#8220;44.\ub85c\uc9c0\uc2a4\ud2f1 \ud68c\uadc0(Logistic Regression), \ubd84\ub958 \ubb38\uc81c\uc5d0\uc11c\uc758 \ub85c\uc9c0\uc2a4\ud2f1 \ud68c\uadc0 \ud65c\uc6a9&#8221;<\/span><\/a><\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"closed","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_jetpack_memberships_contains_paid_content":false,"footnotes":""},"categories":[219],"tags":[],"class_list":["post-40772","post","type-post","status-publish","format-standard","hentry","category-219"],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v26.2 - https:\/\/yoast.com\/wordpress\/plugins\/seo\/ -->\n<title>44.\ub85c\uc9c0\uc2a4\ud2f1 \ud68c\uadc0(Logistic Regression), \ubd84\ub958 \ubb38\uc81c\uc5d0\uc11c\uc758 \ub85c\uc9c0\uc2a4\ud2f1 \ud68c\uadc0 \ud65c\uc6a9 - \ub77c\uc774\ube0c\uc2a4\ub9c8\ud2b8<\/title>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/atmokpo.com\/w\/40772\/\" \/>\n<meta property=\"og:locale\" content=\"ko_KR\" \/>\n<meta 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\ud558\ub098\ub85c \uc81c\ud55c\ub418\uc5b4 \uc788\ub294 \uc0c1\ud669\uc5d0\uc11c \uc8fc\ub85c \ud65c\uc6a9\ub429\ub2c8\ub2e4. \ubcf8 \uac15\uc88c\uc5d0\uc11c\ub294 \ub85c\uc9c0\uc2a4\ud2f1 \ud68c\uadc0\uc758 \uc6d0\ub9ac, \uc218\ud559\uc801 \ubc30\uacbd, \uc2e4\uc81c \uc0ac\ub840, \uc7a5\ub2e8\uc810\uacfc \ud568\uaed8 \uc774\ub97c &hellip; \ub354 \ubcf4\uae30 &quot;44.\ub85c\uc9c0\uc2a4\ud2f1 \ud68c\uadc0(Logistic Regression), \ubd84\ub958 \ubb38\uc81c\uc5d0\uc11c\uc758 \ub85c\uc9c0\uc2a4\ud2f1 \ud68c\uadc0 \ud65c\uc6a9&quot;\" \/>\n<meta property=\"og:url\" content=\"https:\/\/atmokpo.com\/w\/40772\/\" \/>\n<meta property=\"og:site_name\" content=\"\ub77c\uc774\ube0c\uc2a4\ub9c8\ud2b8\" \/>\n<meta property=\"article:published_time\" content=\"2024-11-04T12:20:22+00:00\" \/>\n<meta property=\"article:modified_time\" content=\"2024-11-26T06:38:29+00:00\" \/>\n<meta name=\"author\" content=\"root\" \/>\n<meta name=\"twitter:card\" content=\"summary_large_image\" \/>\n<meta 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