\ub525\ub7ec\ub2dd \ud30c\uc774\ud1a0\uce58 \uac15\uc88c, \ube44\uc9c0\ub3c4 \ud559\uc2b5 - \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\/30054\/\" \/>\n<meta property=\"og:locale\" content=\"ko_KR\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"\ub525\ub7ec\ub2dd \ud30c\uc774\ud1a0\uce58 \uac15\uc88c, \ube44\uc9c0\ub3c4 \ud559\uc2b5 - \ub77c\uc774\ube0c\uc2a4\ub9c8\ud2b8\" \/>\n<meta property=\"og:description\" content=\"\ub525\ub7ec\ub2dd\uc740 \ub370\uc774\ud130\uc5d0\uc11c \ud328\ud134\uc744 \uc790\ub3d9\uc73c\ub85c \ud559\uc2b5\ud558\ub294 \uba38\uc2e0\ub7ec\ub2dd\uc758 \ud55c \ubd84\uc57c\ub85c, \uc785\ub825 \ub370\uc774\ud130\uc5d0\uc11c \uc720\uc775\ud55c \uc815\ubcf4\ub97c \ucd94\ucd9c\ud558\uace0 \uc774\ub97c \uae30\ubc18\uc73c\ub85c \uc608\uce21 \ubc0f \uacb0\uc815\uc744 \ub0b4\ub9ac\ub294 \ubaa8\ub378\uc744 \uc0dd\uc131\ud558\ub294 \uac83\uc744 \ubaa9\ud45c\ub85c \ud569\ub2c8\ub2e4. \uc911\uc5d0\uc11c\ub3c4 \ube44\uc9c0\ub3c4 \ud559\uc2b5(unsupervised learning)\uc740 \ub77c\ubca8\uc774 \uc5c6\ub294 \ub370\uc774\ud130\ub97c \uc774\uc6a9\ud558\uc5ec \ub370\uc774\ud130\uc758 \uad6c\uc870\ub97c \uc774\ud574\ud558\uace0 \uc720\uc0ac\ud55c \uadf8\ub8f9\uc73c\ub85c \ubb36\uc5b4\uc8fc\ub294 \ubc29\ubc95\ub860\uc785\ub2c8\ub2e4. \uc624\ub298\uc740 \ud30c\uc774\ud1a0\uce58\ub97c \ud65c\uc6a9\ud55c \ube44\uc9c0\ub3c4 \ud559\uc2b5\uc758 \uae30\ubcf8 \uac1c\ub150\uacfc \uba87 \uac00\uc9c0 \uc751\uc6a9 \uc608\uc81c\ub97c \uc0b4\ud3b4\ubcf4\uaca0\uc2b5\ub2c8\ub2e4. \ube44\uc9c0\ub3c4 \ud559\uc2b5\uc758 \uac1c\ub150 \ube44\uc9c0\ub3c4 … \ub354 \ubcf4\uae30 "\ub525\ub7ec\ub2dd \ud30c\uc774\ud1a0\uce58 \uac15\uc88c, \ube44\uc9c0\ub3c4 \ud559\uc2b5"\" \/>\n<meta property=\"og:url\" content=\"https:\/\/atmokpo.com\/w\/30054\/\" \/>\n<meta property=\"og:site_name\" content=\"\ub77c\uc774\ube0c\uc2a4\ub9c8\ud2b8\" \/>\n<meta property=\"article:published_time\" content=\"2024-10-28T03:19:22+00:00\" \/>\n<meta property=\"article:modified_time\" content=\"2024-11-26T06:50:13+00:00\" \/>\n<meta name=\"author\" content=\"root\" \/>\n<meta name=\"twitter:card\" content=\"summary_large_image\" \/>\n<meta name=\"twitter:creator\" content=\"@bebubo4\" \/>\n<meta name=\"twitter:site\" content=\"@bebubo4\" \/>\n<meta name=\"twitter:label1\" content=\"\uae00\uc4f4\uc774\" \/>\n\t<meta name=\"twitter:data1\" content=\"root\" \/>\n\t<meta name=\"twitter:label2\" content=\"\uc608\uc0c1 \ub418\ub294 \ud310\ub3c5 \uc2dc\uac04\" \/>\n\t<meta name=\"twitter:data2\" content=\"1\ubd84\" \/>\n<script type=\"application\/ld+json\" class=\"yoast-schema-graph\">{\"@context\":\"https:\/\/schema.org\",\"@graph\":[{\"@type\":\"Article\",\"@id\":\"https:\/\/atmokpo.com\/w\/30054\/#article\",\"isPartOf\":{\"@id\":\"https:\/\/atmokpo.com\/w\/30054\/\"},\"author\":{\"name\":\"root\",\"@id\":\"https:\/\/atmokpo.com\/w\/#\/schema\/person\/91b6b3b138fbba0efb4ae64b1abd81d7\"},\"headline\":\"\ub525\ub7ec\ub2dd \ud30c\uc774\ud1a0\uce58 \uac15\uc88c, \ube44\uc9c0\ub3c4 \ud559\uc2b5\",\"datePublished\":\"2024-10-28T03:19:22+00:00\",\"dateModified\":\"2024-11-26T06:50:13+00:00\",\"mainEntityOfPage\":{\"@id\":\"https:\/\/atmokpo.com\/w\/30054\/\"},\"wordCount\":33,\"publisher\":{\"@id\":\"https:\/\/atmokpo.com\/w\/#organization\"},\"articleSection\":[\"\ud30c\uc774\ud1a0\uce58 \uac15\uc88c\"],\"inLanguage\":\"ko-KR\"},{\"@type\":\"WebPage\",\"@id\":\"https:\/\/atmokpo.com\/w\/30054\/\",\"url\":\"https:\/\/atmokpo.com\/w\/30054\/\",\"name\":\"\ub525\ub7ec\ub2dd \ud30c\uc774\ud1a0\uce58 \uac15\uc88c, \ube44\uc9c0\ub3c4 \ud559\uc2b5 - 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{"id":30054,"date":"2024-10-28T03:19:22","date_gmt":"2024-10-28T03:19:22","guid":{"rendered":"http:\/\/atmokpo.com\/w\/?p=30054"},"modified":"2024-11-26T06:50:13","modified_gmt":"2024-11-26T06:50:13","slug":"%eb%94%a5%eb%9f%ac%eb%8b%9d-%ed%8c%8c%ec%9d%b4%ed%86%a0%ec%b9%98-%ea%b0%95%ec%a2%8c-%eb%b9%84%ec%a7%80%eb%8f%84-%ed%95%99%ec%8a%b5","status":"publish","type":"post","link":"https:\/\/atmokpo.com\/w\/30054\/","title":{"rendered":"\ub525\ub7ec\ub2dd \ud30c\uc774\ud1a0\uce58 \uac15\uc88c, \ube44\uc9c0\ub3c4 \ud559\uc2b5"},"content":{"rendered":"

<\/p>\n

\n \ub525\ub7ec\ub2dd\uc740 \ub370\uc774\ud130\uc5d0\uc11c \ud328\ud134\uc744 \uc790\ub3d9\uc73c\ub85c \ud559\uc2b5\ud558\ub294 \uba38\uc2e0\ub7ec\ub2dd\uc758 \ud55c \ubd84\uc57c\ub85c, \uc785\ub825 \ub370\uc774\ud130\uc5d0\uc11c \uc720\uc775\ud55c \uc815\ubcf4\ub97c \ucd94\ucd9c\ud558\uace0 \uc774\ub97c \uae30\ubc18\uc73c\ub85c \uc608\uce21 \ubc0f \uacb0\uc815\uc744 \ub0b4\ub9ac\ub294 \ubaa8\ub378\uc744 \uc0dd\uc131\ud558\ub294 \uac83\uc744 \ubaa9\ud45c\ub85c \ud569\ub2c8\ub2e4. \uc911\uc5d0\uc11c\ub3c4 \ube44\uc9c0\ub3c4 \ud559\uc2b5(unsupervised learning)\uc740 \ub77c\ubca8\uc774 \uc5c6\ub294 \ub370\uc774\ud130\ub97c \uc774\uc6a9\ud558\uc5ec \ub370\uc774\ud130\uc758 \uad6c\uc870\ub97c \uc774\ud574\ud558\uace0 \uc720\uc0ac\ud55c \uadf8\ub8f9\uc73c\ub85c \ubb36\uc5b4\uc8fc\ub294 \ubc29\ubc95\ub860\uc785\ub2c8\ub2e4. \uc624\ub298\uc740 \ud30c\uc774\ud1a0\uce58\ub97c \ud65c\uc6a9\ud55c \ube44\uc9c0\ub3c4 \ud559\uc2b5\uc758 \uae30\ubcf8 \uac1c\ub150\uacfc \uba87 \uac00\uc9c0 \uc751\uc6a9 \uc608\uc81c\ub97c \uc0b4\ud3b4\ubcf4\uaca0\uc2b5\ub2c8\ub2e4.\n<\/p>\n

\ube44\uc9c0\ub3c4 \ud559\uc2b5\uc758 \uac1c\ub150<\/h2>\n
\n \ube44\uc9c0\ub3c4 \ud559\uc2b5\uc740 \ub370\uc774\ud130\uc5d0 \ub300\ud55c \ub808\uc774\ube14\uc774 \uc8fc\uc5b4\uc9c0\uc9c0 \uc54a\uae30 \ub54c\ubb38\uc5d0 \ubaa8\ub378\uc774 \uc2a4\uc2a4\ub85c \ub370\uc774\ud130\ub97c \ubd84\uc11d\ud558\uc5ec \ud328\ud134\uc744 \ucc3e\uc2b5\ub2c8\ub2e4. \uc774\ub294 \ub370\uc774\ud130\uc758 \uace0\uc720\ud55c \ud2b9\uc131\uacfc \ubd84\ud3ec\ub97c \ud30c\uc545\ud558\ub294 \ub370 \uc8fc\ub825\ud569\ub2c8\ub2e4. \ube44\uc9c0\ub3c4 \ud559\uc2b5\uc758 \uc8fc\uc694 \uc0ac\uc6a9 \uc0ac\ub840\ub85c\ub294 \ud074\ub7ec\uc2a4\ud130\ub9c1(clustering)\uacfc \ucc28\uc6d0 \ucd95\uc18c(dimensionality reduction)\uac00 \uc788\uc2b5\ub2c8\ub2e4.\n<\/p>\n

\ube44\uc9c0\ub3c4 \ud559\uc2b5\uc758 \uc885\ub958<\/h2>\n

\ud074\ub7ec\uc2a4\ud130\ub9c1 (Clustering):<\/strong> \ub370\uc774\ud130 \ud3ec\uc778\ud2b8\ub97c \uc720\uc0ac\uc131\uc5d0 \ub530\ub77c \uadf8\ub8f9\uc73c\ub85c \ub098\ub204\ub294 \ubc29\ubc95\uc785\ub2c8\ub2e4.<\/li>\n
\ucc28\uc6d0 \ucd95\uc18c (Dimensionality Reduction):<\/strong> \ub370\uc774\ud130\uc758 \ucc28\uc6d0\uc744 \uc904\uc5ec\uc11c \uac00\uc7a5 \uc911\uc694\ud55c \uc815\ubcf4\ub9cc \ub0a8\uae30\ub294 \ubc29\ubc95\uc785\ub2c8\ub2e4.<\/li>\n

\uc2e0\ub8b0\ub3c4 \uac80\uc99d (Anomaly Detection):<\/strong> \uc804\uccb4 \ub370\uc774\ud130\uc640 \uc77c\uc815\ud55c \uac70\ub9ac\uac00 \uc788\ub294 \uc774\uc0c1\uce58\ub97c \ud0d0\uc9c0\ud558\ub294 \ubc29\ubc95\uc785\ub2c8\ub2e4.<\/li>\n<\/ul>\n
\ud30c\uc774\ud1a0\uce58(PyTorch) \uc18c\uac1c<\/h2>\n
\n \ud30c\uc774\ud1a0\uce58\ub294 Facebook\uc5d0\uc11c \uac1c\ubc1c\ud55c \ud30c\uc774\uc36c \uae30\ubc18\uc758 \uc624\ud508 \uc18c\uc2a4 \uba38\uc2e0 \ub7ec\ub2dd \ub77c\uc774\ube0c\ub7ec\ub9ac\ub85c, \ud150\uc11c \uacc4\uc0b0\uacfc \ub3d9\uc801 \uc2e0\uacbd\ub9dd \uad6c\ud604\uc5d0 \ub9e4\uc6b0 \uc720\uc6a9\ud569\ub2c8\ub2e4. \ud150\uc11c\ub97c \ud65c\uc6a9\ud55c \uc218\uce58 \uc5f0\uc0b0\uc774 \uac00\ub2a5\ud558\uba70, Compute Graph\ub97c \ub3d9\uc801\uc73c\ub85c \uc0dd\uc131\ud558\uc5ec \ubcf5\uc7a1\ud55c \uc2e0\uacbd\ub9dd \uad6c\uc870\ub97c \uc27d\uac8c \uad6c\ucd95\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4.\n<\/p>\n
\ube44\uc9c0\ub3c4 \ud559\uc2b5 \uc608\uc81c<\/h2>\n
1. K-Means \ud074\ub7ec\uc2a4\ud130\ub9c1<\/h3>\n
\n K-Means\ub294 \uac00\uc7a5 \uc77c\ubc18\uc801\uc778 \ud074\ub7ec\uc2a4\ud130\ub9c1 \uc54c\uace0\ub9ac\uc998 \uc911 \ud558\ub098\uc785\ub2c8\ub2e4. \ub370\uc774\ud130 \ud3ec\uc778\ud2b8\ub97c K\uac1c\uc758 \ud074\ub7ec\uc2a4\ud130\ub85c \ub098\ub204\uace0 \uac01 \ud074\ub7ec\uc2a4\ud130\uc758 \uc911\uc2ec(centroid)\uc744 \uc5c5\ub370\uc774\ud2b8\ud558\ub294 \uacfc\uc815\uc744 \ubc18\ubcf5\ud569\ub2c8\ub2e4. \uc544\ub798\ub294 K-Means \ud074\ub7ec\uc2a4\ud130\ub9c1\uc744 \uad6c\ud604\ud558\ub294 \ud30c\uc774\uc36c \ucf54\ub4dc\uc785\ub2c8\ub2e4.\n<\/p>\n
\n\nimport torch\nimport numpy as np\nimport matplotlib.pyplot as plt\nfrom sklearn.datasets import make_blobs\n\n# \ub370\uc774\ud130 \uc0dd\uc131\nnum_samples = 300\nnum_features = 2\nnum_clusters = 3\n\nX, y = make_blobs(n_samples=num_samples, centers=num_clusters, n_features=num_features, random_state=42)\n\n# K-Means \uc54c\uace0\ub9ac\uc998 \uad6c\ud604\ndef kmeans(X, num_clusters, num_iterations):\n num_samples = X.shape[0]\n centroids = X[np.random.choice(num_samples, num_clusters, replace=False)]\n \n for _ in range(num_iterations):\n distances = torch.cdist(torch.tensor(X), torch.tensor(centroids))\n labels = torch.argmin(distances, dim=1)\n\n for i in range(num_clusters):\n centroids[i] = X[labels == i].mean(axis=0)\n \n return labels, centroids\n\nlabels, centroids = kmeans(X, num_clusters, 10)\n\n# \uacb0\uacfc \uc2dc\uac01\ud654\nplt.scatter(X[:, 0], X[:, 1], c=labels, s=50)\nplt.scatter(centroids[:, 0], centroids[:, 1], c='red', s=200, alpha=0.75, marker='X')\nplt.title('K-Means Clustering')\nplt.show()\n<\/code>\n<\/pre>\n\n \uc704 \ucf54\ub4dc\ub294 `make_blobs` \ud568\uc218\ub97c \uc774\uc6a9\ud558\uc5ec 2D \ud074\ub7ec\uc2a4\ud130 \ub370\uc774\ud130\ub97c \uc0dd\uc131\ud55c \ud6c4, K-Means \uc54c\uace0\ub9ac\uc998\uc744 \ud1b5\ud574 \ud074\ub7ec\uc2a4\ud130\ub9c1\uc744 \uc218\ud589\ud569\ub2c8\ub2e4. \uacb0\uacfc\ub294 \uc2dc\uac01\uc801\uc73c\ub85c \ud655\uc778\ud560 \uc218 \uc788\uc73c\uba70, \ud074\ub7ec\uc2a4\ud130\uc758 \uc911\uc2ec\ub3c4 \ube68\uac04 X\ub85c \ud45c\uc2dc\ub429\ub2c8\ub2e4.\n<\/p>\n 2. PCA (\uc8fc\uc131\ubd84 \ubd84\uc11d)<\/h3>\n\n \uc8fc\uc131\ubd84 \ubd84\uc11d(PCA)\uc740 \ub370\uc774\ud130\ub97c \ub354 \ub0ae\uc740 \ucc28\uc6d0\uc73c\ub85c \ubcc0\ud658\ud558\ub294 \ubc29\ubc95\uc785\ub2c8\ub2e4. \ub370\uc774\ud130\uc758 \ubd84\uc0b0\uc744 \ucd5c\ub300\ud654\ud558\uace0, \ub370\uc774\ud130\uc758 \uad6c\uc870\ub97c \uc720\uc9c0\ud558\uba70 \ucc28\uc6d0\uc744 \ucd95\uc18c\ud568\uc73c\ub85c\uc368 \uc2dc\uac01\ud654\uc640 \ud559\uc2b5 \uc18d\ub3c4\ub97c \uac1c\uc120\ud558\ub294 \ub370 \uc720\uc6a9\ud569\ub2c8\ub2e4.\n<\/p>\n \n\nfrom sklearn.decomposition import PCA\n\n# PCA\ub97c \uc0ac\uc6a9\ud558\uc5ec 2D\ub85c \ucc28\uc6d0 \ucd95\uc18c\npca = PCA(n_components=2)\nX_reduced = pca.fit_transform(X)\n\n# \uacb0\uacfc \uc2dc\uac01\ud654\nplt.scatter(X_reduced[:, 0], X_reduced[:, 1], c=labels, s=50)\nplt.title('PCA Dimensionality Reduction')\nplt.xlabel('Principal Component 1')\nplt.ylabel('Principal Component 2')\nplt.show()\n<\/code>\n<\/pre>\n\n PCA\ub97c \ud1b5\ud574 \ub110\ub9ac \uc0ac\uc6a9\ub418\ub294 \uace0\ucc28\uc6d0 \ub370\uc774\ud130\uc758 \uc2dc\uac01\ud654\ub97c \uc27d\uac8c \uc218\ud589\ud560 \uc218 \uc788\uc73c\uba70, \uad70\uc9d1\ud654 \uc791\uc5c5\uc774 \ud6e8\uc52c \ub354 \uc6a9\uc774\ud574\uc9d1\ub2c8\ub2e4.\n<\/p>\n \ube44\uc9c0\ub3c4 \ud559\uc2b5\uc758 \uc751\uc6a9<\/h2>\n\n \ube44\uc9c0\ub3c4 \ud559\uc2b5 \ubc29\ubc95\ub860\uc740 \ub2e4\uc591\ud55c \ubd84\uc57c\uc5d0 \uc751\uc6a9\ub429\ub2c8\ub2e4. \uc608\ub97c \ub4e4\uc5b4, \uc774\ubbf8\uc9c0 \ubd84\ub958\uc5d0\uc11c \ube44\uc2b7\ud55c \uc774\ubbf8\uc9c0 \uadf8\ub8f9\uc744 \ucc3e\uac70\ub098 \ud14d\uc2a4\ud2b8 \ubd84\uc11d\uc5d0\uc11c \uc8fc\uc81c\ubcc4\ub85c \ubb38\uc11c\ub97c \ud074\ub7ec\uc2a4\ud130\ub9c1\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4. \ud2b9\ud788, \uace0\uac1d \uc138\ubd84\ud654\uc640 \uac19\uc740 \ub9c8\ucf00\ud305 \ubd84\uc57c\uc5d0\uc11c\ub3c4 \ud070 \uc5ed\ud560\uc744 \ud569\ub2c8\ub2e4.\n<\/p>\n \uacb0\ub860<\/h2>\n\n \ube44\uc9c0\ub3c4 \ud559\uc2b5\uc740 \ub370\uc774\ud130\uc758 \uc228\uaca8\uc9c4 \ud328\ud134\uc744 \ucc3e\uace0, \uc0c8\ub85c\uc6b4 \uc778\uc0ac\uc774\ud2b8\ub97c \uc81c\uacf5\ud558\ub294 \uc911\uc694\ud55c \uae30\ubc95\uc785\ub2c8\ub2e4. \ud30c\uc774\ud1a0\uce58\ub97c \ud65c\uc6a9\ud558\uba74 \uc774\ub7ec\ud55c \uae30\ubc95\ub4e4\uc744 \uc190\uc27d\uac8c \uad6c\ud604\ud560 \uc218 \uc788\uc73c\uba70, \ubcf5\uc7a1\ud55c \ubb38\uc81c\ub97c \ud574\uacb0\ud558\ub294 \ub370 \ub3c4\uc6c0\uc744 \uc904 \uc218 \uc788\uc2b5\ub2c8\ub2e4. \uc55e\uc73c\ub85c \ud30c\uc774\ud1a0\uce58\uc640 \uac19\uc740 \ub77c\uc774\ube0c\ub7ec\ub9ac\ub97c \ud65c\uc6a9\ud558\uc5ec \ub354 \ub2e4\uc591\ud55c \ube44\uc9c0\ub3c4 \ud559\uc2b5 \uae30\ubc95\uc744 \uc5f0\uad6c\ud574\ubcf4\ub294 \uac83\uc740 \uc88b\uc740 \uacbd\ud5d8\uc774 \ub420 \uac83\uc785\ub2c8\ub2e4.\n<\/p>\n \ucd94\uac00 \uc790\ub8cc<\/h2>\n\nPyTorch Documentation<\/a><\/li>\n Scikit-Learn Clustering<\/a><\/li>\n Scikit-Learn Decomposition<\/a><\/li>\n<\/ul>\n<\/body><\/p>\n","protected":false},"excerpt":{"rendered":"\ub525\ub7ec\ub2dd\uc740 \ub370\uc774\ud130\uc5d0\uc11c \ud328\ud134\uc744 \uc790\ub3d9\uc73c\ub85c \ud559\uc2b5\ud558\ub294 \uba38\uc2e0\ub7ec\ub2dd\uc758 \ud55c \ubd84\uc57c\ub85c, \uc785\ub825 \ub370\uc774\ud130\uc5d0\uc11c \uc720\uc775\ud55c \uc815\ubcf4\ub97c \ucd94\ucd9c\ud558\uace0 \uc774\ub97c \uae30\ubc18\uc73c\ub85c \uc608\uce21 \ubc0f \uacb0\uc815\uc744 \ub0b4\ub9ac\ub294 \ubaa8\ub378\uc744 \uc0dd\uc131\ud558\ub294 \uac83\uc744 \ubaa9\ud45c\ub85c \ud569\ub2c8\ub2e4. \uc911\uc5d0\uc11c\ub3c4 \ube44\uc9c0\ub3c4 \ud559\uc2b5(unsupervised learning)\uc740 \ub77c\ubca8\uc774 \uc5c6\ub294 \ub370\uc774\ud130\ub97c \uc774\uc6a9\ud558\uc5ec \ub370\uc774\ud130\uc758 \uad6c\uc870\ub97c \uc774\ud574\ud558\uace0 \uc720\uc0ac\ud55c \uadf8\ub8f9\uc73c\ub85c \ubb36\uc5b4\uc8fc\ub294 \ubc29\ubc95\ub860\uc785\ub2c8\ub2e4. \uc624\ub298\uc740 \ud30c\uc774\ud1a0\uce58\ub97c \ud65c\uc6a9\ud55c \ube44\uc9c0\ub3c4 \ud559\uc2b5\uc758 \uae30\ubcf8 \uac1c\ub150\uacfc \uba87 \uac00\uc9c0 \uc751\uc6a9 \uc608\uc81c\ub97c \uc0b4\ud3b4\ubcf4\uaca0\uc2b5\ub2c8\ub2e4. \ube44\uc9c0\ub3c4 \ud559\uc2b5\uc758 \uac1c\ub150 \ube44\uc9c0\ub3c4 … \ub354 \ubcf4\uae30 “\ub525\ub7ec\ub2dd \ud30c\uc774\ud1a0\uce58 \uac15\uc88c, \ube44\uc9c0\ub3c4 \ud559\uc2b5”<\/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":[33],"tags":[],"class_list":["post-30054","post","type-post","status-publish","format-standard","hentry","category-33"],"yoast_head":"\n\ub525\ub7ec\ub2dd \ud30c\uc774\ud1a0\uce58 \uac15\uc88c, \ube44\uc9c0\ub3c4 \ud559\uc2b5 - 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