{"id":31357,"date":"2024-10-28T12:01:30","date_gmt":"2024-10-28T12:01:30","guid":{"rendered":"http:\/\/atmokpo.com\/w\/?p=31357"},"modified":"2024-11-26T06:45:24","modified_gmt":"2024-11-26T06:45:24","slug":"%eb%94%a5%eb%9f%ac%eb%8b%9d%ea%b3%bc-%eb%a8%b8%ec%8b%a0%eb%9f%ac%eb%8b%9d%ec%9d%84-%ed%99%9c%ec%9a%a9%ed%95%9c-%ec%9e%90%eb%8f%99%eb%a7%a4%eb%a7%a4-k-nearest-neighbors-knn%eb%a5%bc-%ed%99%9c","status":"publish","type":"post","link":"https:\/\/atmokpo.com\/w\/31357\/","title":{"rendered":"\ub525\ub7ec\ub2dd\uacfc \uba38\uc2e0\ub7ec\ub2dd\uc744 \ud65c\uc6a9\ud55c \uc790\ub3d9\ub9e4\ub9e4, K-Nearest Neighbors (KNN)\ub97c \ud65c\uc6a9\ud55c \ub9e4\ub9e4 \uc804\ub7b5 \uc720\uc0ac\ud55c \uacfc\uac70 \ub370\uc774\ud130\ub97c \ubc14\ud0d5\uc73c\ub85c \ub9e4\ub9e4 \uc758\uc0ac\uacb0\uc815\ud558\uae30."},"content":{"rendered":"

\ub525\ub7ec\ub2dd\uacfc \uba38\uc2e0\ub7ec\ub2dd\uc744 \ud65c\uc6a9\ud55c \uc790\ub3d9\ub9e4\ub9e4: K-Nearest Neighbors (KNN)\ub97c \ud65c\uc6a9\ud55c \ub9e4\ub9e4 \uc804\ub7b5<\/h2>\n

\uc624\ub298\ub0a0 \uae08\uc735 \uc2dc\uc7a5\uc5d0\uc11c\uc758 \uc790\ub3d9\ub9e4\ub9e4 \uc2dc\uc2a4\ud15c\uc740 \ub370\uc774\ud130 \uacfc\ud559, \ub525\ub7ec\ub2dd, \uba38\uc2e0\ub7ec\ub2dd \ub4f1\uc758 \uae30\uc220\uc744 \ud65c\uc6a9\ud558\uc5ec \uc2dc\uc7a5\uc758 \ubcf5\uc7a1\ud55c \ud328\ud134\uc744 \ud559\uc2b5\ud558\uace0 \uc774\ub97c \uae30\ubc18\uc73c\ub85c \ub9e4\ub9e4 \uacb0\uc815\uc744 \ub0b4\ub9ac\ub294 \ub370 \ud070 \uc5ed\ud560\uc744 \ud558\uace0 \uc788\uc2b5\ub2c8\ub2e4. \ud2b9\ud788 \ube44\ud2b8\ucf54\uc778\uacfc \uac19\uc740 \uc554\ud638\ud654\ud3d0 \uc2dc\uc7a5\uc740 \ubcc0\ub3d9\uc131\uc774 \ud06c\uace0 \uae09\uaca9\ud55c \uac00\uaca9 \ubcc0\ud654\uac00 \uc7a6\uc544 \uc774\ub7f0 \uae30\uc220\ub4e4\uc774 \ub354\uc6b1 \uc911\uc694\ud558\uac8c \uc791\uc6a9\ud569\ub2c8\ub2e4. \ubcf8 \uac15\uc88c\uc5d0\uc11c\ub294 K-Nearest Neighbors (KNN) \uc54c\uace0\ub9ac\uc998\uc744 \ud65c\uc6a9\ud558\uc5ec \uc720\uc0ac\ud55c \uacfc\uac70 \ub370\uc774\ud130\ub97c \ubd84\uc11d\ud568\uc73c\ub85c\uc368 \ube44\ud2b8\ucf54\uc778 \ub9e4\ub9e4 \uc804\ub7b5\uc744 \uc124\uacc4\ud558\ub294 \ubc29\ubc95\uc5d0 \ub300\ud574 \uc54c\uc544\ubcf4\uaca0\uc2b5\ub2c8\ub2e4.<\/p>\n

1. K-Nearest Neighbors (KNN) \uc54c\uace0\ub9ac\uc998 \uac1c\uc694<\/h3>\n

KNN\uc740 \uba38\uc2e0\ub7ec\ub2dd\uc758 \ube44\uc9c0\ub3c4 \ud559\uc2b5 \uae30\ubc95 \uc911 \ud558\ub098\ub85c, \uc8fc\uc5b4\uc9c4 \ub370\uc774\ud130\ub97c \uae30\ubc18\uc73c\ub85c \uc720\uc0ac\ud55c \ub370\uc774\ud130\ub97c \ucc3e\uc544 \uc608\uce21\ud558\ub294 \ubc29\ubc95\uc785\ub2c8\ub2e4. KNN\uc758 \ud575\uc2ec \uc544\uc774\ub514\uc5b4\ub294 \uc0c8\ub85c\uc6b4 \ub370\uc774\ud130 \ud3ec\uc778\ud2b8\uac00 \uc8fc\uc5b4\uc84c\uc744 \ub54c, \uc774\uc6c3 \ub370\uc774\ud130 \ud3ec\uc778\ud2b8 \uc911 \uac00\uc7a5 \uac00\uae4c\uc6b4 K\uac1c\ub97c \ucc3e\uc544 \uadf8 \uc911 \ub2e4\uc218\uc758 \ud074\ub798\uc2a4\ub97c \uacb0\uacfc\ub85c \uacb0\uc815\ud558\ub294 \uac83\uc785\ub2c8\ub2e4. KNN\uc740 \uc8fc\ub85c \ubd84\ub958 \ubb38\uc81c\uc5d0 \ub9ce\uc774 \uc0ac\uc6a9\ub418\uc9c0\ub9cc, \ud68c\uadc0 \ubb38\uc81c\uc5d0\ub3c4 \ud65c\uc6a9\ub420 \uc218 \uc788\uc2b5\ub2c8\ub2e4.<\/p>\n

2. KNN\uc758 \uc6d0\ub9ac<\/h3>\n

KNN \uc54c\uace0\ub9ac\uc998\uc740 \ub2e4\uc74c\uacfc \uac19\uc740 \ub2e8\uacc4\ub85c \uc791\ub3d9\ud569\ub2c8\ub2e4:<\/p>\n

    \n
  1. \ub370\uc774\ud130 \uc138\ud2b8\uc5d0\uc11c \ubaa8\ub4e0 \ud3ec\uc778\ud2b8 \uac04\uc758 \uac70\ub9ac\ub97c \uacc4\uc0b0\ud569\ub2c8\ub2e4.<\/li>\n
  2. \uc8fc\uc5b4\uc9c4 \ud3ec\uc778\ud2b8\uc640 \uac00\uc7a5 \uac00\uae4c\uc6b4 K\uac1c\uc758 \uc774\uc6c3\uc744 \uc120\ud0dd\ud569\ub2c8\ub2e4.<\/li>\n
  3. \uac00\uc7a5 \ub9ce\uc774 \ub4f1\uc7a5\ud558\ub294 \ud074\ub798\uc2a4\ub098 \ud3c9\uade0 \uac12\uc744 \ubc18\ud658\ud558\uc5ec \uc608\uce21\ud569\ub2c8\ub2e4.<\/li>\n<\/ol>\n

    KNN\uc758 \uc8fc\uc694\ud55c \uc7a5\uc810\uc740 \uad6c\ud604\uc774 \uac04\ub2e8\ud558\uace0 \uc774\ud574\ud558\uae30 \uc27d\ub2e4\ub294 \uac83\uc785\ub2c8\ub2e4. \ud558\uc9c0\ub9cc \ub2e8\uc810\uc73c\ub85c\ub294 \ub370\uc774\ud130\uac00 \ub9ce\uc544\uc9c8\uc218\ub85d \uacc4\uc0b0 \ube44\uc6a9\uc774 \uc0c1\uc2b9\ud558\uace0, \ucc28\uc6d0\uc758 \uc800\uc8fc \ubb38\uc81c\uc5d0 \ubbfc\uac10\ud558\ub2e4\ub294 \uac83\uc774 \uc788\uc2b5\ub2c8\ub2e4.<\/p>\n

    3. \uc790\ub3d9\ub9e4\ub9e4 \uc2dc\uc2a4\ud15c \uc124\uacc4<\/h3>\n

    \ube44\ud2b8\ucf54\uc778 \uc790\ub3d9\ub9e4\ub9e4 \uc2dc\uc2a4\ud15c\uc744 \uc124\uacc4\ud558\uae30 \uc704\ud574\uc11c\ub294 \ub2e4\uc74c\uacfc \uac19\uc740 \ub2e8\uacc4\ub97c \uac70\uccd0\uc57c \ud569\ub2c8\ub2e4:<\/p>\n

      \n
    1. \ub370\uc774\ud130 \uc218\uc9d1: \ube44\ud2b8\ucf54\uc778\uc758 \uc5ed\uc0ac\uc801 \uac00\uaca9 \ub370\uc774\ud130\ub97c \uc218\uc9d1\ud569\ub2c8\ub2e4.<\/li>\n
    2. \ub370\uc774\ud130 \uc804\ucc98\ub9ac: \uc218\uc9d1\ud55c \ub370\uc774\ud130\ub97c \uc815\ub9ac\ud558\uace0 KNN \ubaa8\ub378\uc5d0 \uc801\ud569\ud55c \ud615\uc2dd\uc73c\ub85c \ubcc0\ud658\ud569\ub2c8\ub2e4.<\/li>\n
    3. \ubaa8\ub378 \ud559\uc2b5: KNN \uc54c\uace0\ub9ac\uc998\uc744 \uc0ac\uc6a9\ud558\uc5ec \uacfc\uac70 \ub370\uc774\ud130\ub97c \uae30\ubc18\uc73c\ub85c \ubaa8\ub378\uc744 \ud559\uc2b5\uc2dc\ud0b5\ub2c8\ub2e4.<\/li>\n
    4. \ub9e4\ub9e4 \uc804\ub7b5 \uc218\ub9bd: \uc608\uce21\ub41c \uacb0\uacfc\ub97c \uae30\ubc18\uc73c\ub85c \ub9e4\ub9e4 \uacb0\uc815\uc744 \ub0b4\ub9ac\ub294 \uc54c\uace0\ub9ac\uc998\uc744 \uc124\uacc4\ud569\ub2c8\ub2e4.<\/li>\n<\/ol>\n

      4. \ub370\uc774\ud130 \uc218\uc9d1<\/h3>\n

      \ube44\ud2b8\ucf54\uc778 \uac00\uaca9 \ub370\uc774\ud130\ub97c \uc218\uc9d1\ud558\uae30 \uc704\ud574\uc11c\ub294 \ub2e4\uc591\ud55c \ub370\uc774\ud130 \uc81c\uacf5 API\ub97c \uc0ac\uc6a9\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4. \uc5ec\uae30\uc11c\ub294 \ud30c\uc774\uc36c\uc744 \uc0ac\uc6a9\ud558\uc5ec \ucf54\uc778\uac8c\ucf54(CoinGecko) API\ub97c \ud1b5\ud574 \ub370\uc774\ud130\ub97c \uac00\uc838\uc624\ub294 \ubc29\ubc95\uc744 \uc18c\uac1c\ud558\uaca0\uc2b5\ub2c8\ub2e4. \uc544\ub798\uc758 \ucf54\ub4dc\ub294 \ube44\ud2b8\ucf54\uc778\uc758 \uc77c\uc77c \uac00\uaca9 \ub370\uc774\ud130\ub97c \uc218\uc9d1\ud558\ub294 \uc608\uc81c\uc785\ub2c8\ub2e4:<\/p>\n

      import requests\nimport pandas as pd\nfrom datetime import datetime\n\n# API \ud638\ucd9c\nurl = 'https:\/\/api.coingecko.com\/api\/v3\/coins\/bitcoin\/market_chart'\nparams = {\n    'vs_currency': 'usd',\n    'days': '30',  # \ub9c8\uc9c0\ub9c9 30\uc77c \ub370\uc774\ud130\n    'interval': 'daily'\n}\nresponse = requests.get(url, params=params)\ndata = response.json()\n\n# \ub370\uc774\ud130\ud504\ub808\uc784 \uc0dd\uc131\nprices = data['prices']\ndf = pd.DataFrame(prices, columns=['timestamp', 'price'])\n\n# \ud0c0\uc784\uc2a4\ud0ec\ud504 \ubcc0\ud658\ndf['timestamp'] = pd.to_datetime(df['timestamp'], unit='ms')\n\n# \ub370\uc774\ud130 \ucd9c\ub825\nprint(df.head())<\/code><\/pre>\n
      5. \ub370\uc774\ud130 \uc804\ucc98\ub9ac<\/h3>\n
      \uc218\uc9d1\ub41c \ub370\uc774\ud130\ub294 \uc774\uc0c1\uac12 \uc81c\uac70, \uacb0\uce21\uac12 \ucc98\ub9ac \ubc0f \ud2b9\uc131 \uc5d4\uc9c0\ub2c8\uc5b4\ub9c1\uc744 \ud1b5\ud574 \ubaa8\ub378\uc5d0 \uc801\ud569\ud55c \ud615\ud0dc\ub85c \ubcc0\ud658\ud574\uc57c \ud569\ub2c8\ub2e4. \uc608\ub97c \ub4e4\uc5b4, \uac00\uaca9 \ub370\uc774\ud130\ub97c \uae30\ubc18\uc73c\ub85c \uae30\uc220\uc801 \uc9c0\ud45c\ub97c \ucd94\uac00\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4. \ubcf4\ud1b5 \uc0ac\uc6a9\ud558\ub294 \uae30\uc220\uc801 \uc9c0\ud45c\ub294 \uc774\ub3d9 \ud3c9\uade0(MA), \uc0c1\ub300\uac15\ub3c4\uc9c0\uc218(RSI), MACD \ub4f1\uc774 \uc788\uc2b5\ub2c8\ub2e4. \uc544\ub798 \ucf54\ub4dc\ub294 \uc774\ub3d9 \ud3c9\uade0\uc744 \ucd94\uac00\ud558\ub294 \uc608\uc81c\uc785\ub2c8\ub2e4:<\/p>\n
      # \uc774\ub3d9 \ud3c9\uade0 \ucd94\uac00\ndf['MA_10'] = df['price'].rolling(window=10).mean()\ndf['MA_50'] = df['price'].rolling(window=50).mean()\ndf.dropna(inplace=True)\n<\/code><\/pre>\n
      6. KNN \ubaa8\ub378 \ud559\uc2b5<\/h3>\n
      \ub370\uc774\ud130\uac00 \uc900\ube44\ub418\uba74 KNN \ubaa8\ub378\uc744 \ud559\uc2b5\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4. \uc774\ub97c \uc704\ud574 sklearn \ub77c\uc774\ube0c\ub7ec\ub9ac\ub97c \uc0ac\uc6a9\ud560 \uc218 \uc788\uc73c\uba70, K \uc218\uce58\ub294 \uc2e4\ud5d8\uc744 \ud1b5\ud574 \ucd5c\uc801\ud654\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4. \uc544\ub798\ub294 KNN \ubaa8\ub378\uc744 \ud559\uc2b5\ud558\uace0 \uc608\uce21\ud558\ub294 \ucf54\ub4dc\uc785\ub2c8\ub2e4:<\/p>\n
      from sklearn.model_selection import train_test_split\nfrom sklearn.neighbors import KNeighborsClassifier\nfrom sklearn.metrics import classification_report\n\n# \ud2b9\uc131\uacfc \ub808\uc774\ube14 \ubd84\ub9ac\nX = df[['MA_10', 'MA_50']].values\ny = (df['price'].shift(-1) > df['price']).astype(int)  # \ub2e4\uc74c \ub0a0 \uac00\uaca9\uc774 \uc0c1\uc2b9\ud558\uba74 1, \ud558\ub77d\ud558\uba74 0\n\n# \ud6c8\ub828 \uc138\ud2b8\uc640 \ud14c\uc2a4\ud2b8 \uc138\ud2b8\ub85c \ubd84\ub9ac\nX_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.2, random_state=42)\n\n# KNN \ubaa8\ub378 \ud559\uc2b5\nknn = KNeighborsClassifier(n_neighbors=5)\nknn.fit(X_train, y_train)\n\n# \uc608\uce21 \ubc0f \ud3c9\uac00\ny_pred = knn.predict(X_test)\nprint(classification_report(y_test, y_pred))<\/code><\/pre>\n
      7. \ub9e4\ub9e4 \uc804\ub7b5 \uad6c\ud604<\/h3>\n
      \ubaa8\ub378\uc758 \uc608\uce21 \uacb0\uacfc\ub97c \ubc14\ud0d5\uc73c\ub85c \ub9e4\ub9e4 \uacb0\uc815\uc744 \ub0b4\ub9ac\ub294 \uc54c\uace0\ub9ac\uc998\uc744 \uad6c\ud604\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4. \uc608\ub97c \ub4e4\uc5b4, \ubaa8\ub378\uc774 \ube44\ud2b8\ucf54\uc778\uc758 \uac00\uaca9\uc774 \uc0c1\uc2b9\ud560 \uac83\uc774\ub77c\uace0 \uc608\uce21\ud560 \uacbd\uc6b0 \ub9e4\uc218\ud558\uace0, \ud558\ub77d\ud560 \uac83\uc774\ub77c\uace0 \uc608\uce21\ud560 \uacbd\uc6b0 \ub9e4\ub3c4\ud558\ub294 \uac04\ub2e8\ud55c \uc804\ub7b5\uc744 \uc0dd\uac01\ud574\ubcfc \uc218 \uc788\uc2b5\ub2c8\ub2e4:<\/p>\n
      def trading_signal(prediction):\n    if prediction == 1:\n        return 'Buy'  # \uc0c1\uc2b9 \uc608\uce21\n    else:\n        return 'Sell'  # \ud558\ub77d \uc608\uce21\n\n# \ub9c8\uc9c0\ub9c9 \ub370\uc774\ud130\uc5d0 \ub300\ud55c \uc2e0\ud638 \uc0dd\uc131\nlast_prediction = knn.predict(X[-1].reshape(1, -1))\nsignal = trading_signal(last_prediction[0])\nprint(f\"Trading Signal: {signal}\")<\/code><\/pre>\n
      8. \uc131\ub2a5 \ud3c9\uac00<\/h3>\n
      \ub9e4\ub9e4 \uc804\ub7b5\uc758 \uc131\ub2a5\uc740 \ub2e4\uc591\ud55c \uc9c0\ud45c\ub97c \ud1b5\ud574 \ud3c9\uac00\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4. \uc218\uc775\ub960, \uc0e4\ud504 \ube44\uc728, \ucd5c\ub300 \ub099\ud3ed \ub4f1\uc744 \uace0\ub824\ud560 \uc218 \uc788\uc73c\uba70, \uc2e4\ud5d8\uc801\uc778 \ubc31\ud14c\uc2a4\ud305 \ubc29\uc2dd\uc744 \ud1b5\ud574 \uc804\ub7b5\uc758 \uc720\ud6a8\uc131\uc744 \uac80\uc99d\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4. \uacfc\uac70 \ub370\uc774\ud130\ub97c \uae30\ubc18\uc73c\ub85c \uc2dc\ubbac\ub808\uc774\uc158\uc744 \uc2dc\ud589\ud558\uc5ec \ub9e4\ub9e4 \uacb0\uacfc\ub97c \ubd84\uc11d\ud558\ub294 \ucf54\ub4dc \uc608\ub294 \ub2e4\uc74c\uacfc \uac19\uc2b5\ub2c8\ub2e4:<\/p>\n
      initial_balance = 1000  # \ucd08\uae30 \ud22c\uc790\uae08\nbalance = initial_balance\n\nfor i in range(len(X_test)):\n    if y_pred[i] == 1:  # Buy\n        balance *= (1 + (df['price'].iloc[i+len(X_train)] - df['price'].iloc[i+len(X_train)-1]) \/ df['price'].iloc[i+len(X_train)-1])\n    else:  # Sell\n        balance *= (1 - (df['price'].iloc[i+len(X_train)] - df['price'].iloc[i+len(X_train)-1]) \/ df['price'].iloc[i+len(X_train)-1])\n\nfinal_balance = balance\nprofit = final_balance - initial_balance\nprint(f\"Initial Balance: {initial_balance}, Final Balance: {final_balance}, Profit: {profit}\")<\/code><\/pre>\n
      9. \uacb0\ub860<\/h3>\n
      KNN\uc740 \uac04\ub2e8\ud558\uba74\uc11c\ub3c4 \ud6a8\uacfc\uc801\uc778 \uba38\uc2e0\ub7ec\ub2dd \uc54c\uace0\ub9ac\uc998\uc73c\ub85c, \ube44\ud2b8\ucf54\uc778 \uc790\ub3d9\ub9e4\ub9e4 \uc804\ub7b5\uc744 \uc138\uc6b0\ub294 \ub370 \uc720\uc6a9\ud55c \ub3c4\uad6c\uac00 \ub420 \uc218 \uc788\uc2b5\ub2c8\ub2e4. \ubcf8 \uac15\uc88c\uc5d0\uc11c \uc18c\uac1c\ud55c \ubc29\ubc95\uc744 \ud1b5\ud574 \uc790\ub3d9\ub9e4\ub9e4 \uc2dc\uc2a4\ud15c\uc744 \uad6c\ucd95\ud558\uace0 KNN\uc744 \ud65c\uc6a9\ud55c \ub9e4\ub9e4 \uc804\ub7b5\uc744 \uc218\ub9bd\ud558\ub294 \ubc29\ubc95\uc744 \ubc30\uc6cc\ubcf4\uc558\uc2b5\ub2c8\ub2e4. \ud558\uc9c0\ub9cc KNN\ub9cc\uc73c\ub85c\ub294 \ud55c\uacc4\uac00 \uc788\uc744 \uc218 \uc788\uc73c\ubbc0\ub85c, \ub2e4\ub978 \uc54c\uace0\ub9ac\uc998\uacfc \uacb0\ud569\ud558\uac70\ub098 \uc559\uc0c1\ube14 \uae30\ubc95\uc744 \ud1b5\ud574 \ub354\uc6b1 \uc815\uad50\ud55c \uc804\ub7b5\uc744 \uac1c\ubc1c\ud558\ub294 \uac83\uc744 \uad8c\uc7a5\ud569\ub2c8\ub2e4. \uae30\uc874\uc758 \ub9e4\ub9e4 \uc804\ub7b5\uc744 \uc9c0\uc18d\uc801\uc73c\ub85c \uac80\uc99d\ud558\uace0 \uc870\uc815\ud558\ub294 \uac83\ub3c4 \uc911\uc694\ud569\ub2c8\ub2e4.<\/p>\n
      \ube44\ud2b8\ucf54\uc778 \uc790\ub3d9\ub9e4\ub9e4\uc5d0 \ub300\ud55c \ub354 \ub9ce\uc740 \uc815\ubcf4\uc640 \uc804\ub7b5\uc744 \uc6d0\ud558\uc2e0\ub2e4\uba74, \uad00\ub828 \ubb38\ud5cc\uacfc \uc5f0\uad6c \uc790\ub8cc\ub97c \ucc38\uace0\ud558\uc5ec \uae4a\uc774 \uc788\ub294 \uc9c0\uc2dd\uc744 \ud655\uc7a5\ud574 \ub098\uac00\uc2dc\uae30 \ubc14\ub78d\ub2c8\ub2e4.<\/p>\n