{"id":28773,"date":"2024-10-27T16:14:59","date_gmt":"2024-10-27T16:14:59","guid":{"rendered":"http:\/\/atmokpo.com\/w\/?p=28773"},"modified":"2024-11-26T06:57:53","modified_gmt":"2024-11-26T06:57:53","slug":"%eb%a8%b8%ec%8b%a0%eb%9f%ac%eb%8b%9d-%eb%b0%8f-%eb%94%a5%eb%9f%ac%eb%8b%9d-%ec%95%8c%ea%b3%a0%eb%a6%ac%ec%a6%98-%ed%8a%b8%eb%a0%88%ec%9d%b4%eb%94%a9-%ea%b0%80%ec%9a%b0%ec%8a%a4-%eb%a7%88%eb%a5%b4","status":"publish","type":"post","link":"https:\/\/atmokpo.com\/w\/28773\/","title":{"rendered":"\uba38\uc2e0\ub7ec\ub2dd \ubc0f \ub525\ub7ec\ub2dd \uc54c\uace0\ub9ac\uc998 \ud2b8\ub808\uc774\ub529, \uac00\uc6b0\uc2a4-\ub9c8\ub974\ucf54\ud504 \uc815\ub9ac"},"content":{"rendered":"

<\/p>\n

1. \uc11c\ub860<\/h2>\n

\ucd5c\uadfc \uc218\ub144\uac04 \uae08\uc735 \uc2dc\uc7a5\uc740 \uba38\uc2e0\ub7ec\ub2dd\uacfc \ub525\ub7ec\ub2dd\uc758 \ubc1c\uc804\uc5d0 \ub530\ub77c \uae09\uaca9\ud558\uac8c \ubcc0\ud654\ud558\uace0 \uc788\uc2b5\ub2c8\ub2e4. \uc774 \uae00\uc5d0\uc11c\ub294 \uc54c\uace0\ub9ac\uc998 \ud2b8\ub808\uc774\ub529\uc5d0\uc11c \uba38\uc2e0\ub7ec\ub2dd\uacfc \ub525\ub7ec\ub2dd \uae30\ubc95\uc744 \ud65c\uc6a9\ud558\ub294 \ubc29\ubc95\uc5d0 \ub300\ud574 \uc124\uba85\ud558\uace0, \uac00\uc6b0\uc2a4-\ub9c8\ub974\ucf54\ud504 \uc815\ub9ac\uc758 \uc911\uc694\uc131\uacfc \uc774\ub97c \ud65c\uc6a9\ud55c \ub370\uc774\ud130 \ubd84\uc11d \uae30\ubc95\uc744 \uc18c\uac1c\ud569\ub2c8\ub2e4.<\/p>\n

2. \uba38\uc2e0\ub7ec\ub2dd\uacfc \ub525\ub7ec\ub2dd \uae30\ucd08<\/h2>\n

2.1 \uba38\uc2e0\ub7ec\ub2dd \uae30\ubcf8 \uac1c\ub150<\/h3>\n

\uba38\uc2e0\ub7ec\ub2dd\uc740 \ub370\uc774\ud130\ub97c \ubd84\uc11d\ud558\uace0 \ud328\ud134\uc744 \ud559\uc2b5\ud558\uc5ec \uc608\uce21 \ubaa8\ub378\uc744 \ub9cc\ub4dc\ub294 \uae30\uacc4 \ud559\uc2b5\uc758 \ud55c \ubd84\uc57c\uc785\ub2c8\ub2e4. \uc54c\uace0\ub9ac\uc998\uc740 \uacfc\uac70 \ub370\uc774\ud130\ub97c \uae30\ubc18\uc73c\ub85c \ud559\uc2b5\ud558\uace0, \uc774\ub97c \ud1b5\ud574 \ubbf8\ub798 \ub370\uc774\ud130\ub97c \uc608\uce21\ud560 \uc218 \uc788\ub294 \ub2a5\ub825\uc744 \uac16\ucd94\uac8c \ub429\ub2c8\ub2e4. \uc8fc\ub85c \uc9c0\ub3c4 \ud559\uc2b5, \ube44\uc9c0\ub3c4 \ud559\uc2b5, \uac15\ud654 \ud559\uc2b5 \ub4f1\uc73c\ub85c \ub098\ub258\uc5b4\uc9d1\ub2c8\ub2e4.<\/p>\n

2.2 \ub525\ub7ec\ub2dd \uae30\ubcf8 \uac1c\ub150<\/h3>\n

\ub525\ub7ec\ub2dd\uc740 \uc778\uacf5\uc2e0\uacbd\ub9dd(ANN)\uc744 \uae30\ubc18\uc73c\ub85c \ud558\ub294 \uba38\uc2e0\ub7ec\ub2dd\uc758 \ud558\uc704 \ubd84\uc57c\ub85c, \ub2e4\uc911 \uce35\uc758 \uc2e0\uacbd\ub9dd\uc744 \ud65c\uc6a9\ud558\uc5ec \ub370\uc774\ud130\uc5d0\uc11c \ubcf5\uc7a1\ud55c \ud328\ud134\uc744 \ud559\uc2b5\ud569\ub2c8\ub2e4. \uc774\ubbf8\uc9c0 \uc778\uc2dd, \uc790\uc5f0\uc5b4 \ucc98\ub9ac \ub4f1 \ub2e4\uc591\ud55c \ubd84\uc57c\uc5d0\uc11c \ub110\ub9ac \uc0ac\uc6a9\ub418\uace0 \uc788\uc2b5\ub2c8\ub2e4.<\/p>\n

3. \uac00\uc6b0\uc2a4-\ub9c8\ub974\ucf54\ud504 \uc815\ub9ac\ub780?<\/h2>\n

\uac00\uc6b0\uc2a4-\ub9c8\ub974\ucf54\ud504 \uc815\ub9ac\ub294 \uc120\ud615 \ud68c\uadc0 \ubd84\uc11d\uc5d0\uc11c \uac00\uc7a5 \uc911\uc694\ud55c \ud1b5\uacc4\uc801 \uc774\ub860 \uc911 \ud558\ub098\ub85c, \uc624\ucc28\uac00 \uc815\uaddc \ubd84\ud3ec\ub97c \ub530\ub974\uba70 \ub3c5\ub9bd\uc801\uc774\uace0 \ub3d9\uc77c\ud558\uac8c \ubd84\ud3ec(\ub3c5\ub9bd\uc131 \uac00\uc815)\ub97c \ub9cc\uc871\ud560 \uacbd\uc6b0, \ucd5c\uc18c \uc81c\uacf1 \ucd94\uc815\ub7c9\uc774 \uac00\uc7a5 \uc791\uc740 \ubd84\uc0b0\uc744 \uac16\ub294 \ubd88\ud3b8 \ucd94\uc815\ub7c9\uc774\ub77c\ub294 \uac83\uc744 \ub9d0\ud569\ub2c8\ub2e4.<\/p>\n

3.1 \uac00\uc6b0\uc2a4-\ub9c8\ub974\ucf54\ud504 \uc815\ub9ac\uc758 \uc218\ud559\uc801 \ud45c\ud604<\/h3>\n
\n    \u03b8 = (X'X)\u207b\u00b9X'y\n    <\/code><\/pre>\n
\uc5ec\uae30\uc11c \u03b8\ub294 \ud68c\uadc0 \uacc4\uc218, X\ub294 \uc124\uba85 \ubcc0\uc218 \ud589\ub82c, y\ub294 \uc885\uc18d \ubcc0\uc218 \ubca1\ud130\ub97c \ub098\ud0c0\ub0c5\ub2c8\ub2e4. \uc774 \uc2dd\uc744 \ud1b5\ud574 \ucd5c\uc801\uc758 \ud68c\uadc0 \uacc4\uc218\ub97c \ucd94\uc815\ud560 \uc218 \uc788\uc73c\uba70, \uc774\ub294 \uc608\uce21\uc758 \uc815\ud655\uc131\uc744 \ub192\uc774\ub294 \ud575\uc2ec \uc694\uc18c\uc785\ub2c8\ub2e4.<\/p>\n
4. \uac00\uc6b0\uc2a4-\ub9c8\ub974\ucf54\ud504 \uc815\ub9ac\uc758 \ud65c\uc6a9<\/h2>\n
\uac00\uc6b0\uc2a4-\ub9c8\ub974\ucf54\ud504 \uc815\ub9ac\ub294 \uae08\uc735 \ub370\uc774\ud130 \ubd84\uc11d \ubc0f \uc54c\uace0\ub9ac\uc998 \ud2b8\ub808\uc774\ub529\uc5d0\uc11c \ub9e4\uc6b0 \uc720\uc6a9\ud569\ub2c8\ub2e4. \uba38\uc2e0\ub7ec\ub2dd \ubc0f \ub525\ub7ec\ub2dd \ubaa8\ub378\uc744 \uad6c\ucd95\ud558\uace0 \uc774\ub97c \ud3c9\uac00\ud558\ub294 \ub370 \uc788\uc5b4, \uac00\uc6b0\uc2a4-\ub9c8\ub974\ucf54\ud504 \uc815\ub9ac\uc5d0\uc11c \uc720\ub3c4\ub41c \uacb0\uacfc\ub97c \ud65c\uc6a9\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4.<\/p>\n
4.1 \uae08\uc735 \uc2dc\uc7a5\uc5d0\uc11c\uc758 \ud68c\uadc0 \ubd84\uc11d<\/h3>\n
\ud68c\uadc0 \ubd84\uc11d\uc740 \uc8fc\uc2dd \uac00\uaca9 \uc608\uce21, \ub9ac\uc2a4\ud06c \uad00\ub9ac \ubc0f \uc790\uc0b0 \ubc30\ubd84 \ub4f1 \ub2e4\uc591\ud55c \uae08\uc735 \ubd84\uc57c\uc5d0\uc11c \ud65c\uc6a9\ub429\ub2c8\ub2e4. \uac00\uc6b0\uc2a4-\ub9c8\ub974\ucf54\ud504 \uc815\ub9ac\uc5d0 \uae30\ubc18\ud558\uc5ec Linear Regression \ubaa8\ub378\uc744 \uad6c\ucd95\ud558\uba74, \ub370\uc774\ud130\uc758 \ud328\ud134\uc744 \ud1b5\ud574 \ubbf8\ub798\uc758 \uc8fc\uc2dd \uac00\uaca9\uc744 \ubcf4\ub2e4 \uc815\ud655\ud558\uac8c \uc608\uce21\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4.<\/p>\n
5. \uba38\uc2e0\ub7ec\ub2dd \uc54c\uace0\ub9ac\uc998 \ud2b8\ub808\uc774\ub529 \uc124\uacc4<\/h2>\n
\uba38\uc2e0\ub7ec\ub2dd\uc744 \ud65c\uc6a9\ud55c \uc54c\uace0\ub9ac\uc998 \ud2b8\ub808\uc774\ub529 \uc2dc\uc2a4\ud15c\uc758 \uc124\uacc4 \uacfc\uc815\uc740 \ub2e4\uc74c\uacfc \uac19\uc740 \ub2e8\uacc4\ub85c \ub098\ub20c \uc218 \uc788\uc2b5\ub2c8\ub2e4:<\/p>\n
    \n
  1. \ub370\uc774\ud130 \uc218\uc9d1: \uae08\uc735 \ub370\uc774\ud130(\uc8fc\uc2dd \uac00\uaca9, \uac70\ub798\ub7c9 \ub4f1)\ub97c \uc218\uc9d1\ud558\ub294 \ub2e8\uacc4\uc785\ub2c8\ub2e4.<\/li>\n
  2. \ub370\uc774\ud130 \uc804\ucc98\ub9ac: \uacb0\uce21\uce58 \uc81c\uac70, \uc774\uc0c1\uce58 \ucc98\ub9ac, \uc815\uaddc\ud654 \ub4f1\uc758 \uc791\uc5c5\uc744 \ud1b5\ud574 \uba38\uc2e0\ub7ec\ub2dd \ubaa8\ub378\uc5d0 \uc801\ud569\ud55c \ud615\ud0dc\ub85c \ub370\uc774\ud130\ub97c \ubcc0\ud658\ud569\ub2c8\ub2e4.<\/li>\n
  3. \ubaa8\ub378 \uc120\ud0dd: \ud68c\uadc0 \ubaa8\ub378, \uc758\uc0ac\uacb0\uc815 \ub098\ubb34, \uc2e0\uacbd\ub9dd \ub4f1 \ub2e4\uc591\ud55c \uc54c\uace0\ub9ac\uc998 \uc911\uc5d0\uc11c \uc801\ud569\ud55c \ubaa8\ub378\uc744 \uc120\ud0dd\ud569\ub2c8\ub2e4.<\/li>\n
  4. \ubaa8\ub378 \ud559\uc2b5: \uc120\ud0dd\ud55c \ubaa8\ub378\uc744 \ud1b5\ud574 \ub370\uc774\ud130\ub97c \ud559\uc2b5\uc2dc\ud0b5\ub2c8\ub2e4.<\/li>\n
  5. \ubaa8\ub378 \ud3c9\uac00: \ud559\uc2b5\ub41c \ubaa8\ub378\uc758 \uc131\ub2a5\uc744 \ud3c9\uac00\ud558\ub294 \ub2e8\uacc4\ub85c, \uad50\ucc28 \uac80\uc99d \ub4f1\uc758 \ubc29\ubc95\uc744 \uc0ac\uc6a9\ud569\ub2c8\ub2e4.<\/li>\n
  6. \ubaa8\ub378 \ucd5c\uc801\ud654: \ubaa8\ub378 \uc131\ub2a5\uc744 \ud5a5\uc0c1\uc2dc\ud0a4\uae30 \uc704\ud55c \ud558\uc774\ud37c\ud30c\ub77c\ubbf8\ud130 \ud29c\ub2dd \uc791\uc5c5\uc744 \uc9c4\ud589\ud569\ub2c8\ub2e4.<\/li>\n
  7. \uc2e4\uc2dc\uac04 \uac70\ub798:** \uc885\ub8cc\ub41c \ubaa8\ub378\uc744 \uc2e4\uc81c \uc2dc\uc7a5\uc5d0\uc11c \uc801\uc6a9\ud558\uc5ec \uc790\ub3d9\uc73c\ub85c \uac70\ub798\ub97c \uc218\ud589\ud569\ub2c8\ub2e4.<\/li>\n<\/ol>\n
    5.1 \uba38\uc2e0\ub7ec\ub2dd \ubaa8\ub378 \uc608\uc81c<\/h3>\n
    \ub2e4\uc74c\uc740 Python\uc744 \uc0ac\uc6a9\ud55c \uc8fc\uc2dd \uac00\uaca9 \uc608\uce21\uc744 \uc704\ud55c \uba38\uc2e0\ub7ec\ub2dd \ubaa8\ub378\uc758 \uc608\uc81c \ucf54\ub4dc\uc785\ub2c8\ub2e4.<\/p>\n
    \n    import pandas as pd\n    from sklearn.model_selection import train_test_split\n    from sklearn.linear_model import LinearRegression\n\n    # \ub370\uc774\ud130 \uc218\uc9d1\n    data = pd.read_csv('stock_data.csv')\n\n    # \ub370\uc774\ud130 \uc804\ucc98\ub9ac\n    X = data[['feature1', 'feature2']]\n    y = data['target']\n\n    # \ud559\uc2b5\uc6a9 \ub370\uc774\ud130\uc640 \ud14c\uc2a4\ud2b8\uc6a9 \ub370\uc774\ud130 \ubd84\ub9ac\n    X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.2, random_state=42)\n\n    # \ubaa8\ub378 \uc120\ud0dd \ubc0f \ud559\uc2b5\n    model = LinearRegression()\n    model.fit(X_train, y_train)\n\n    # \ubaa8\ub378 \ud3c9\uac00\n    score = model.score(X_test, y_test)\n    print(f'Model Accuracy: {score}')\n    <\/code><\/pre>\n
    6. \ub525\ub7ec\ub2dd \uc54c\uace0\ub9ac\uc998 \ud2b8\ub808\uc774\ub529 \uc124\uacc4<\/h2>\n
    \ub525\ub7ec\ub2dd \uae30\ubc18\uc758 \uc54c\uace0\ub9ac\uc998 \ud2b8\ub808\uc774\ub529 \uc2dc\uc2a4\ud15c\ub3c4 \uba38\uc2e0\ub7ec\ub2dd\uacfc \uc720\uc0ac\ud55c \ub2e8\uacc4\ub97c \uac70\uce69\ub2c8\ub2e4. \uadf8\ub7ec\ub098 \ub370\uc774\ud130 \uc804\ucc98\ub9ac \ub2e8\uacc4\uc5d0\uc11c\ub294 \uc8fc\ub85c \uc2e0\uacbd\ub9dd\uc758 \uc785\ub825 \ud615\ud0dc\uc5d0 \ub9de\ub294 \ub370\uc774\ud130\ub97c \uad6c\uc131\ud558\ub294 \uac83\uc774 \uc911\uc694\ud569\ub2c8\ub2e4.<\/p>\n
    6.1 \ub525\ub7ec\ub2dd \ubaa8\ub378 \uc608\uc81c<\/h3>\n
    \uc544\ub798\ub294 Keras\ub97c \uc0ac\uc6a9\ud55c \uac04\ub2e8\ud55c LSTM(Long Short-Term Memory) \ubaa8\ub378\uc758 \uc608\uc81c \ucf54\ub4dc\uc785\ub2c8\ub2e4.<\/p>\n
    \n    from keras.models import Sequential\n    from keras.layers import LSTM, Dense\n    import numpy as np\n\n    # \ub370\uc774\ud130 \uc900\ube44\n    X = np.random.rand(1000, 10, 1)  # 1000\uac1c\uc758 \uc0d8\ud50c, 10\uac1c\uc758 \ud0c0\uc784\uc2a4\ud15d\n    y = np.random.rand(1000)\n\n    # LSTM \ubaa8\ub378 \uad6c\uc131\n    model = Sequential()\n    model.add(LSTM(50, activation='relu', input_shape=(X.shape[1], 1)))\n    model.add(Dense(1))\n\n    # \ubaa8\ub378 \ucef4\ud30c\uc77c\n    model.compile(optimizer='adam', loss='mse')\n\n    # \ubaa8\ub378 \ud559\uc2b5\n    model.fit(X, y, epochs=200, batch_size=32)\n    <\/code><\/pre>\n
    7. \uacb0\ub860<\/h2>\n
    \uba38\uc2e0\ub7ec\ub2dd\uacfc \ub525\ub7ec\ub2dd\uc744 \ud65c\uc6a9\ud55c \uc54c\uace0\ub9ac\uc998 \ud2b8\ub808\uc774\ub529\uc740 \ub370\uc774\ud130 \ubd84\uc11d \ubc0f \uc608\uce21 \ubaa8\ub378\ub9c1\uc758 \uac15\ub825\ud55c \ub3c4\uad6c\uc785\ub2c8\ub2e4. \uac00\uc6b0\uc2a4-\ub9c8\ub974\ucf54\ud504 \uc815\ub9ac\uc5d0 \uae30\ubc18\ud55c \ud68c\uadc0 \ubd84\uc11d\uc740 \uc774\ub7ec\ud55c \ubaa8\ub378\uc744 \uad6c\ucd95\ud558\ub294 \ub370 \uc788\uc5b4 \ud544\uc218\uc801\uc778 \uc774\ub860\uc73c\ub85c, \uae08\uc735 \ub370\uc774\ud130\uc758 \ud328\ud134\uc744 \uc774\ud574\ud558\uace0 \uc608\uce21\ud558\ub294 \ub370 \ud070 \ub3c4\uc6c0\uc744 \uc90d\ub2c8\ub2e4. \uba38\uc2e0\ub7ec\ub2dd\uacfc \ub525\ub7ec\ub2dd\uc744 \ud1b5\ud574 \ubc1c\uc804\ud558\ub294 \uc54c\uace0\ub9ac\uc998 \ud2b8\ub808\uc774\ub529\uc758 \uc138\uacc4\ub294 \uc55e\uc73c\ub85c\ub3c4 \ub9ce\uc740 \uac00\ub2a5\uc131\uacfc \uae30\ud68c\ub97c \uc81c\uacf5\ud560 \uac83\uc785\ub2c8\ub2e4.<\/p>\n
    8. \ucc38\uace0\uc790\ub8cc<\/h2>\n
    \uc774\ubc88 \uac15\uc88c\uc5d0 \uc0ac\uc6a9\ub41c \uc790\ub8cc \ubc0f \ucd94\ucc9c \uc11c\uc801\uc740 \ub2e4\uc74c\uacfc \uac19\uc2b5\ub2c8\ub2e4:<\/p>\n