배터리_XGBoost.ipynb

{
  "nbformat": 4,
  "nbformat_minor": 0,
  "metadata": {
    "colab": {
      "provenance": [],
      "gpuType": "A100"
    },
    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
    },
    "language_info": {
      "name": "python"
    },
    "accelerator": "GPU"
  },
  "cells": [
    {
      "cell_type": "code",
      "source": [
        "import numpy as np\n",
        "import os\n",
        "import xgboost as xgb\n",
        "from sklearn.model_selection import train_test_split\n",
        "from sklearn.metrics import accuracy_score"
      ],
      "metadata": {
        "id": "j3cpY5oq4aEJ"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "### 데이터 로드"
      ],
      "metadata": {
        "id": "TqaXazBq4eoz"
      }
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "ZgG6idh5r720",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "a059e22d-a957-4d89-f7da-fa6ea64af672"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "✅ 데이터 로드 성공!\n",
            "📂 normal_arr shape: (770977, 98)\n",
            "📂 caution_arr shape: (584051, 98)\n",
            "📂 defect_arr shape: (584498, 98)\n"
          ]
        }
      ],
      "source": [
        "import numpy as np\n",
        "\n",
        "# 1. 데이터 로드\n",
        "normal_arr = np.load(\"/content/drive/MyDrive/list/train_normal_arr.npy\")\n",
        "caution_arr = np.load(\"/content/drive/MyDrive/list/train_caution_arr.npy\")\n",
        "defect_arr = np.load(\"/content/drive/MyDrive/list/train_defect_arr.npy\")\n",
        "\n",
        "# 데이터 로드 성공 메시지 및 shape 확인\n",
        "print(\"✅ 데이터 로드 성공!\")\n",
        "print(f\"📂 normal_arr shape: {normal_arr.shape}\")\n",
        "print(f\"📂 caution_arr shape: {caution_arr.shape}\")\n",
        "print(f\"📂 defect_arr shape: {defect_arr.shape}\")\n"
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "### 👽 슬라이딩 윈도우 처리한 것 새로운 데이터 형성"
      ],
      "metadata": {
        "id": "GchqBryZ4rCW"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "import os\n",
        "# ✅ 2. 슬라이딩 윈도우 함수 정의\n",
        "def create_sliding_windows(arr, window_size=100, step=30):\n",
        "    \"\"\" 시계열 데이터를 윈도우 크기로 슬라이싱하는 함수 \"\"\"\n",
        "    n_rows = arr.shape[0]  # 총 데이터 개수\n",
        "    windows = []  # 결과 저장 리스트\n",
        "    for i in range(0, n_rows - window_size + 1, step):  # step 만큼 이동하며 윈도우 생성\n",
        "        windows.append(arr[i:i+window_size])\n",
        "    return np.array(windows)  # 리스트를 numpy 배열로 변환\n",
        "\n",
        "# ✅ 3. 각 데이터에 대해 슬라이딩 윈도우 적용 (새로운 데이터)\n",
        "normal_windows = create_sliding_windows(normal_arr, window_size=100, step=30)\n",
        "caution_windows = create_sliding_windows(caution_arr, window_size=100, step=30)\n",
        "defect_windows = create_sliding_windows(defect_arr, window_size=100, step=30)\n",
        "\n",
        "print(\"\\n✅ 슬라이딩 윈도우 적용 완료!\")\n",
        "print(f\"📂 normal_windows shape: {normal_windows.shape}\")\n",
        "print(f\"📂 caution_windows shape: {caution_windows.shape}\")\n",
        "print(f\"📂 defect_windows shape: {defect_windows.shape}\")\n",
        "\n",
        "# ✅ 4. 슬라이딩 윈도우 데이터를 새로운 .npy 파일로 저장\n",
        "save_dir = \"/content/drive/MyDrive/list/sliding_window_data\"  # 저장할 폴더 경로\n",
        "os.makedirs(save_dir, exist_ok=True)  # 폴더 없으면 생성\n",
        "\n",
        "np.save(os.path.join(save_dir, \"train_normal_windows.npy\"), normal_windows)\n",
        "np.save(os.path.join(save_dir, \"train_caution_windows.npy\"), caution_windows)\n",
        "np.save(os.path.join(save_dir, \"train_defect_windows.npy\"), defect_windows)\n",
        "\n",
        "print(\"\\n✅ 새로운 슬라이딩 윈도우 데이터 저장 완료!\")\n",
        "print(f\"📂 저장 경로: {save_dir}\")\n"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "EtAbwoj5t-t-",
        "outputId": "fcca9a4d-f3a2-40f7-fdc4-0a056bd12f98"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "\n",
            "✅ 슬라이딩 윈도우 적용 완료!\n",
            "📂 normal_windows shape: (25696, 100, 98)\n",
            "📂 caution_windows shape: (19466, 100, 98)\n",
            "📂 defect_windows shape: (19480, 100, 98)\n",
            "\n",
            "✅ 새로운 슬라이딩 윈도우 데이터 저장 완료!\n",
            "📂 저장 경로: /content/drive/MyDrive/list/sliding_window_data\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "## XGBoost -> 2D만 적용 가능! + 마지막에 시각화"
      ],
      "metadata": {
        "id": "9v50RBeb4MWC"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "import matplotlib.pyplot as plt\n",
        "import numpy as np\n",
        "import xgboost as xgb\n",
        "from sklearn.model_selection import train_test_split\n",
        "from sklearn.metrics import accuracy_score\n",
        "\n",
        "# ✅ 1. 슬라이딩 윈도우 데이터 불러오기\n",
        "normal_windows = np.load(\"/content/drive/MyDrive/list/sliding_window_data/train_normal_windows.npy\")\n",
        "caution_windows = np.load(\"/content/drive/MyDrive/list/sliding_window_data/train_caution_windows.npy\")\n",
        "defect_windows = np.load(\"/content/drive/MyDrive/list/sliding_window_data/train_defect_windows.npy\")\n",
        "\n",
        "# ✅ 2. 각 데이터에 대한 라벨 생성\n",
        "normal_labels = np.zeros(len(normal_windows))   # 정상 (0)\n",
        "caution_labels = np.ones(len(caution_windows))  # 주의 (1)\n",
        "defect_labels = np.full(len(defect_windows), 2) # 결함 (2)\n",
        "\n",
        "# ✅ 3. 데이터를 합쳐서 최종 X, y 생성\n",
        "X = np.concatenate([normal_windows, caution_windows, defect_windows], axis=0)\n",
        "y = np.concatenate([normal_labels, caution_labels, defect_labels], axis=0)\n",
        "\n",
        "# ✅ 4. 3D 데이터를 2D로 변환 (XGBoost 입력 형식 맞추기)\n",
        "X = X.reshape(X.shape[0], -1)\n",
        "\n",
        "# ✅ 5. Train-Test Split (학습 데이터 & 테스트 데이터 분할)\n",
        "X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.2, random_state=42)\n",
        "\n",
        "# ✅ 6. XGBoost 하이퍼파라미터 설정\n",
        "params = {\n",
        "    \"objective\": \"multi:softmax\",  # 다중 클래스 분류 (0, 1, 2)\n",
        "    \"num_class\": 3,  # 클래스 개수\n",
        "    \"eval_metric\": \"mlogloss\",  # 다중 클래스 로그 손실\n",
        "    \"max_depth\": 10,  # 트리 깊이\n",
        "    \"eta\": 0.1,  # 학습률\n",
        "    \"subsample\": 1.0,  # 샘플링 비율\n",
        "    \"colsample_bytree\": 1.0,  # 트리 생성 시 사용할 특성 비율\n",
        "    \"random_state\": 42  # 랜덤 시드\n",
        "}\n",
        "\n",
        "# ✅ 7. XGBoost 데이터 변환\n",
        "dtrain = xgb.DMatrix(X_train, label=y_train)\n",
        "dtest = xgb.DMatrix(X_test, label=y_test)\n",
        "\n",
        "# ✅ 8. XGBoost 모델 학습 (조기 종료 포함)\n",
        "early_stopping_rounds = 10  # 10번 동안 개선이 없으면 멈춤\n",
        "evals_result = {}  # 학습 로그 저장\n",
        "\n",
        "print(\"\\n🚀 XGBoost 모델 학습 시작...\")\n",
        "model = xgb.train(\n",
        "    params,\n",
        "    dtrain,\n",
        "    num_boost_round=150,\n",
        "    evals=[(dtest, \"Test\")],\n",
        "    early_stopping_rounds=early_stopping_rounds,\n",
        "    evals_result=evals_result,  # 학습 결과 저장\n",
        "    verbose_eval=1\n",
        ")\n",
        "\n",
        "# ✅ 9. 예측 수행\n",
        "y_pred = model.predict(dtest)\n",
        "\n",
        "# ✅ 10. 모델 정확도 평가\n",
        "accuracy = accuracy_score(y_test, y_pred)\n",
        "print(f\"\\n🎯 XGBoost 모델 정확도: {accuracy:.4f}\")\n",
        "\n",
        "# ✅ 11. `Test-mlogloss` 시각화 (Loss 그래프)\n",
        "plt.figure(figsize=(10, 5))\n",
        "plt.plot(evals_result[\"Test\"][\"mlogloss\"], label=\"Test-mlogloss\", marker=\"o\")\n",
        "plt.xlabel(\"Boosting Rounds\")\n",
        "plt.ylabel(\"Multi-class Log Loss\")\n",
        "plt.title(\"XGBoost Test Loss over Iterations\")\n",
        "plt.legend()\n",
        "plt.grid(True)\n",
        "plt.show()\n",
        "\n",
        "# ✅ 12. `accuracy` 시각화 (막대 그래프)\n",
        "plt.figure(figsize=(5, 5))\n",
        "plt.bar([\"Test Accuracy\"], [accuracy], color=[\"blue\"])\n",
        "plt.ylim(0, 1)\n",
        "plt.ylabel(\"Accuracy\")\n",
        "plt.title(\"Final Model Accuracy\")\n",
        "plt.grid(axis=\"y\")\n",
        "plt.show()\n"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1000
        },
        "id": "AbcE9qPH9_WH",
        "outputId": "1ff8395f-baa1-4257-ff97-7aff5b25f0f7"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "\n",
            "🚀 XGBoost 모델 학습 시작...\n",
            "[0]\tTest-mlogloss:1.00569\n",
            "[1]\tTest-mlogloss:0.92450\n",
            "[2]\tTest-mlogloss:0.85359\n",
            "[3]\tTest-mlogloss:0.79139\n",
            "[4]\tTest-mlogloss:0.73615\n",
            "[5]\tTest-mlogloss:0.68636\n",
            "[6]\tTest-mlogloss:0.64316\n",
            "[7]\tTest-mlogloss:0.60277\n",
            "[8]\tTest-mlogloss:0.56462\n",
            "[9]\tTest-mlogloss:0.53262\n",
            "[10]\tTest-mlogloss:0.50085\n",
            "[11]\tTest-mlogloss:0.47384\n",
            "[12]\tTest-mlogloss:0.44964\n",
            "[13]\tTest-mlogloss:0.42551\n",
            "[14]\tTest-mlogloss:0.40095\n",
            "[15]\tTest-mlogloss:0.38291\n",
            "[16]\tTest-mlogloss:0.36239\n",
            "[17]\tTest-mlogloss:0.34429\n",
            "[18]\tTest-mlogloss:0.32919\n",
            "[19]\tTest-mlogloss:0.31435\n",
            "[20]\tTest-mlogloss:0.30039\n",
            "[21]\tTest-mlogloss:0.28733\n",
            "[22]\tTest-mlogloss:0.27511\n",
            "[23]\tTest-mlogloss:0.26392\n",
            "[24]\tTest-mlogloss:0.25378\n",
            "[25]\tTest-mlogloss:0.24352\n",
            "[26]\tTest-mlogloss:0.23424\n",
            "[27]\tTest-mlogloss:0.22533\n",
            "[28]\tTest-mlogloss:0.21739\n",
            "[29]\tTest-mlogloss:0.20969\n",
            "[30]\tTest-mlogloss:0.20226\n",
            "[31]\tTest-mlogloss:0.19536\n",
            "[32]\tTest-mlogloss:0.18842\n",
            "[33]\tTest-mlogloss:0.18171\n",
            "[34]\tTest-mlogloss:0.17598\n",
            "[35]\tTest-mlogloss:0.17107\n",
            "[36]\tTest-mlogloss:0.16613\n",
            "[37]\tTest-mlogloss:0.16045\n",
            "[38]\tTest-mlogloss:0.15566\n",
            "[39]\tTest-mlogloss:0.15079\n",
            "[40]\tTest-mlogloss:0.14586\n",
            "[41]\tTest-mlogloss:0.14137\n",
            "[42]\tTest-mlogloss:0.13738\n",
            "[43]\tTest-mlogloss:0.13299\n",
            "[44]\tTest-mlogloss:0.12954\n",
            "[45]\tTest-mlogloss:0.12626\n",
            "[46]\tTest-mlogloss:0.12318\n",
            "[47]\tTest-mlogloss:0.11966\n",
            "[48]\tTest-mlogloss:0.11655\n",
            "[49]\tTest-mlogloss:0.11327\n",
            "[50]\tTest-mlogloss:0.10960\n",
            "[51]\tTest-mlogloss:0.10671\n",
            "[52]\tTest-mlogloss:0.10371\n",
            "[53]\tTest-mlogloss:0.10028\n",
            "[54]\tTest-mlogloss:0.09795\n",
            "[55]\tTest-mlogloss:0.09584\n",
            "[56]\tTest-mlogloss:0.09314\n",
            "[57]\tTest-mlogloss:0.09006\n",
            "[58]\tTest-mlogloss:0.08739\n",
            "[59]\tTest-mlogloss:0.08495\n",
            "[60]\tTest-mlogloss:0.08287\n",
            "[61]\tTest-mlogloss:0.08073\n",
            "[62]\tTest-mlogloss:0.07871\n",
            "[63]\tTest-mlogloss:0.07660\n",
            "[64]\tTest-mlogloss:0.07517\n",
            "[65]\tTest-mlogloss:0.07323\n",
            "[66]\tTest-mlogloss:0.07058\n",
            "[67]\tTest-mlogloss:0.06854\n",
            "[68]\tTest-mlogloss:0.06680\n",
            "[69]\tTest-mlogloss:0.06544\n",
            "[70]\tTest-mlogloss:0.06397\n",
            "[71]\tTest-mlogloss:0.06203\n",
            "[72]\tTest-mlogloss:0.06059\n",
            "[73]\tTest-mlogloss:0.05917\n",
            "[74]\tTest-mlogloss:0.05807\n",
            "[75]\tTest-mlogloss:0.05677\n",
            "[76]\tTest-mlogloss:0.05525\n",
            "[77]\tTest-mlogloss:0.05409\n",
            "[78]\tTest-mlogloss:0.05313\n",
            "[79]\tTest-mlogloss:0.05198\n",
            "[80]\tTest-mlogloss:0.05067\n",
            "[81]\tTest-mlogloss:0.04944\n",
            "[82]\tTest-mlogloss:0.04841\n",
            "[83]\tTest-mlogloss:0.04749\n",
            "[84]\tTest-mlogloss:0.04640\n",
            "[85]\tTest-mlogloss:0.04523\n",
            "[86]\tTest-mlogloss:0.04409\n",
            "[87]\tTest-mlogloss:0.04342\n",
            "[88]\tTest-mlogloss:0.04224\n",
            "[89]\tTest-mlogloss:0.04124\n",
            "[90]\tTest-mlogloss:0.04032\n",
            "[91]\tTest-mlogloss:0.03920\n",
            "[92]\tTest-mlogloss:0.03836\n",
            "[93]\tTest-mlogloss:0.03756\n",
            "[94]\tTest-mlogloss:0.03703\n",
            "[95]\tTest-mlogloss:0.03617\n",
            "[96]\tTest-mlogloss:0.03549\n",
            "[97]\tTest-mlogloss:0.03459\n",
            "[98]\tTest-mlogloss:0.03390\n",
            "[99]\tTest-mlogloss:0.03327\n",
            "[100]\tTest-mlogloss:0.03266\n",
            "[101]\tTest-mlogloss:0.03193\n",
            "[102]\tTest-mlogloss:0.03129\n",
            "[103]\tTest-mlogloss:0.03073\n",
            "[104]\tTest-mlogloss:0.03008\n",
            "[105]\tTest-mlogloss:0.02948\n",
            "[106]\tTest-mlogloss:0.02878\n",
            "[107]\tTest-mlogloss:0.02794\n",
            "[108]\tTest-mlogloss:0.02729\n",
            "[109]\tTest-mlogloss:0.02658\n",
            "[110]\tTest-mlogloss:0.02609\n",
            "[111]\tTest-mlogloss:0.02541\n",
            "[112]\tTest-mlogloss:0.02490\n",
            "[113]\tTest-mlogloss:0.02435\n",
            "[114]\tTest-mlogloss:0.02390\n",
            "[115]\tTest-mlogloss:0.02350\n",
            "[116]\tTest-mlogloss:0.02294\n",
            "[117]\tTest-mlogloss:0.02241\n",
            "[118]\tTest-mlogloss:0.02201\n",
            "[119]\tTest-mlogloss:0.02159\n",
            "[120]\tTest-mlogloss:0.02119\n",
            "[121]\tTest-mlogloss:0.02087\n",
            "[122]\tTest-mlogloss:0.02044\n",
            "[123]\tTest-mlogloss:0.02005\n",
            "[124]\tTest-mlogloss:0.01971\n",
            "[125]\tTest-mlogloss:0.01932\n",
            "[126]\tTest-mlogloss:0.01897\n",
            "[127]\tTest-mlogloss:0.01866\n",
            "[128]\tTest-mlogloss:0.01843\n",
            "[129]\tTest-mlogloss:0.01809\n",
            "[130]\tTest-mlogloss:0.01780\n",
            "[131]\tTest-mlogloss:0.01748\n",
            "[132]\tTest-mlogloss:0.01724\n",
            "[133]\tTest-mlogloss:0.01700\n",
            "[134]\tTest-mlogloss:0.01684\n",
            "[135]\tTest-mlogloss:0.01657\n",
            "[136]\tTest-mlogloss:0.01635\n",
            "[137]\tTest-mlogloss:0.01604\n",
            "[138]\tTest-mlogloss:0.01586\n",
            "[139]\tTest-mlogloss:0.01573\n",
            "[140]\tTest-mlogloss:0.01547\n",
            "[141]\tTest-mlogloss:0.01510\n",
            "[142]\tTest-mlogloss:0.01484\n",
            "[143]\tTest-mlogloss:0.01461\n",
            "[144]\tTest-mlogloss:0.01442\n",
            "[145]\tTest-mlogloss:0.01420\n",
            "[146]\tTest-mlogloss:0.01395\n",
            "[147]\tTest-mlogloss:0.01374\n",
            "[148]\tTest-mlogloss:0.01357\n",
            "[149]\tTest-mlogloss:0.01339\n",
            "\n",
            "🎯 XGBoost 모델 정확도: 0.9981\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1000x500 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 500x500 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "### 1. Feature Importance + 시각화"
      ],
      "metadata": {
        "id": "-qCM7qSq_tWJ"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "import matplotlib.pyplot as plt\n",
        "import xgboost as xgb\n",
        "import numpy as np"
      ],
      "metadata": {
        "id": "7XDRES4z_0GZ"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "# ✅ XGBoost 모델에서 Feature Importance 가져오기\n",
        "feature_importance = model.get_score(importance_type=\"weight\")\n",
        "\n",
        "# ✅ Feature Importance를 정렬하여 그래프 그리기\n",
        "sorted_features = sorted(feature_importance.items(), key=lambda x: x[1], reverse=True)\n",
        "feature_names, feature_scores = zip(*sorted_features)\n",
        "\n",
        "plt.figure(figsize=(12, 6))\n",
        "plt.barh(feature_names[:20], feature_scores[:20], color=plt.cm.Paired(np.linspace(0, 1, len(feature_scores[:20]))))\n",
        "plt.xlabel(\"Importance Score\")\n",
        "plt.ylabel(\"Feature\")\n",
        "plt.title(\"Top 20 Feature Importance (XGBoost)\")\n",
        "plt.gca().invert_yaxis()  # 중요도가 높은 순서로 정렬\n",
        "plt.grid(True, linestyle=\"--\", alpha=0.6)\n",
        "plt.show()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 564
        },
        "id": "cnZu43Pm_wbT",
        "outputId": "3dd4a9b1-992f-4d86-d7e4-2d921458a40c"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1200x600 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "### 2. SHAP + 시각화"
      ],
      "metadata": {
        "id": "d1Q_0GV8_3LU"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "import shap"
      ],
      "metadata": {
        "id": "Fpu3BqU6__oT"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "# ✅ SHAP 분석을 위한 객체 생성\n",
        "explainer = shap.Explainer(model, X_train)\n",
        "shap_values = explainer(X_test)\n",
        "\n",
        "# ✅ SHAP Summary Plot (전체 Feature 영향력 분석)\n",
        "plt.figure(figsize=(12, 6))\n",
        "shap.summary_plot(shap_values, X_test, plot_type=\"dot\", show=True)\n"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 733
        },
        "id": "nFF95VfG_5td",
        "outputId": "f96d7245-e8b6-4144-b7c4-ea419e4661e8"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "100%|===================| 38765/38787 [20:56<00:00]       "
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1200x600 with 0 Axes>"
            ]
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1150x660 with 3 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    }
  ]
}