removed-nb

Untitled.ipynb

@@ -1,107 +0,0 @@
-{
- "cells": [
-  {
-   "cell_type": "code",
-   "execution_count": 7,
-   "id": "6de1a7e2-d47b-4de4-a006-882bc270d9d3",
-   "metadata": {},
-   "outputs": [
-    {
-     "ename": "ModuleNotFoundError",
-     "evalue": "No module named 'xgboost'",
-     "output_type": "error",
-     "traceback": [
-      "\u001b[31m---------------------------------------------------------------------------\u001b[39m",
-      "\u001b[31mModuleNotFoundError\u001b[39m                       Traceback (most recent call last)",
-      "\u001b[36mCell\u001b[39m\u001b[36m \u001b[39m\u001b[32mIn[7]\u001b[39m\u001b[32m, line 3\u001b[39m\n\u001b[32m      1\u001b[39m \u001b[38;5;28;01mfrom\u001b[39;00m\u001b[38;5;250m \u001b[39m\u001b[34;01mA5\u001b[39;00m\u001b[34;01m.\u001b[39;00m\u001b[34;01mCorrelationFilter\u001b[39;00m\u001b[38;5;250m \u001b[39m\u001b[38;5;28;01mimport\u001b[39;00m CorrelationFilter\n\u001b[32m      2\u001b[39m \u001b[38;5;28;01mimport\u001b[39;00m\u001b[38;5;250m \u001b[39m\u001b[34;01mpickle\u001b[39;00m\n\u001b[32m----> \u001b[39m\u001b[32m3\u001b[39m \u001b[38;5;28;01mimport\u001b[39;00m\u001b[38;5;250m \u001b[39m\u001b[34;01mxgboost\u001b[39;00m\u001b[38;5;250m \u001b[39m\u001b[38;5;28;01mas\u001b[39;00m\u001b[38;5;250m \u001b[39m\u001b[34;01mxgb\u001b[39;00m\n\u001b[32m      4\u001b[39m \u001b[38;5;28;01mimport\u001b[39;00m\u001b[38;5;250m \u001b[39m\u001b[34;01mlightgbm\u001b[39;00m\u001b[38;5;250m \u001b[39m\u001b[38;5;28;01mas\u001b[39;00m\u001b[38;5;250m \u001b[39m\u001b[34;01mlgb\u001b[39;00m\n\u001b[32m      5\u001b[39m \u001b[38;5;28;01mwith\u001b[39;00m \u001b[38;5;28mopen\u001b[39m(\u001b[33m\"\u001b[39m\u001b[33mA5/models/ensemble_classification_champion.pkl\u001b[39m\u001b[33m\"\u001b[39m, \u001b[33m\"\u001b[39m\u001b[33mrb\u001b[39m\u001b[33m\"\u001b[39m) \u001b[38;5;28;01mas\u001b[39;00m f:\n",
-      "\u001b[31mModuleNotFoundError\u001b[39m: No module named 'xgboost'"
-     ]
-    }
-   ],
-   "source": []
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 8,
-   "id": "dff0f7ab-3b6e-4299-a61e-bb49a895167f",
-   "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "Collecting xgboost\n",
-      "  Downloading xgboost-3.2.0-py3-none-macosx_12_0_arm64.whl.metadata (2.1 kB)\n",
-      "Collecting lightgbm\n",
-      "  Downloading lightgbm-4.6.0-py3-none-macosx_12_0_arm64.whl.metadata (17 kB)\n",
-      "Requirement already satisfied: numpy in /Users/reemothman/miniconda3/lib/python3.12/site-packages (from xgboost) (1.26.4)\n",
-      "Requirement already satisfied: scipy in /Users/reemothman/miniconda3/lib/python3.12/site-packages (from xgboost) (1.17.0)\n",
-      "Downloading xgboost-3.2.0-py3-none-macosx_12_0_arm64.whl (2.3 MB)\n",
-      "\u001b[2K   \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m2.3/2.3 MB\u001b[0m \u001b[31m23.8 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
-      "\u001b[?25hDownloading lightgbm-4.6.0-py3-none-macosx_12_0_arm64.whl (1.6 MB)\n",
-      "\u001b[2K   \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m1.6/1.6 MB\u001b[0m \u001b[31m26.9 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
-      "\u001b[?25hInstalling collected packages: xgboost, lightgbm\n",
-      "Successfully installed lightgbm-4.6.0 xgboost-3.2.0\n"
-     ]
-    }
-   ],
-   "source": [
-    "!pip install xgboost lightgbm"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 9,
-   "id": "d93e2239-29aa-434e-a82f-cc00cde6064a",
-   "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "dict_keys(['model', 'model_name', 'scaler', 'feature_columns', 'cv_metrics', 'test_metrics', 'a4_champion_f1', 'improvement_pct'])\n"
-     ]
-    }
-   ],
-   "source": [
-    "from A5.CorrelationFilter import CorrelationFilter\n",
-    "import pickle\n",
-    "import xgboost as xgb\n",
-    "import lightgbm as lgb\n",
-    "with open(\"A5/models/ensemble_classification_champion.pkl\", \"rb\") as f:\n",
-    "    artifact = pickle.load(f)\n",
-    "\n",
-    "print(artifact.keys())"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "b96efe6a-86f0-4e45-94ed-98ff1da1b8e9",
-   "metadata": {},
-   "outputs": [],
-   "source": []
-  }
- ],
- "metadata": {
-  "kernelspec": {
-   "display_name": "Python 3 (ipykernel)",
-   "language": "python",
-   "name": "python3"
-  },
-  "language_info": {
-   "codemirror_mode": {
-    "name": "ipython",
-    "version": 3
-   },
-   "file_extension": ".py",
-   "mimetype": "text/x-python",
-   "name": "python",
-   "nbconvert_exporter": "python",
-   "pygments_lexer": "ipython3",
-   "version": "3.12.8"
-  }
- },
- "nbformat": 4,
- "nbformat_minor": 5
-}