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prediction/short_term_outcome_prediction/explorations/xgb_gridsearch_evaluation.ipynb
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,121 @@ | ||
| { | ||
| "cells": [ | ||
| { | ||
| "cell_type": "code", | ||
| "execution_count": null, | ||
| "id": "initial_id", | ||
| "metadata": { | ||
| "ExecuteTime": { | ||
| "end_time": "2024-08-23T10:34:57.630025Z", | ||
| "start_time": "2024-08-23T10:34:57.627164Z" | ||
| } | ||
| }, | ||
| "outputs": [], | ||
| "source": [ | ||
| "import matplotlib.pyplot as plt\n", | ||
| "import pandas as pd\n", | ||
| "import os\n", | ||
| "import seaborn as sns" | ||
| ] | ||
| }, | ||
| { | ||
| "cell_type": "code", | ||
| "execution_count": null, | ||
| "id": "b7dfd825b243cf65", | ||
| "metadata": { | ||
| "ExecuteTime": { | ||
| "end_time": "2024-08-23T10:35:30.472389Z", | ||
| "start_time": "2024-08-23T10:35:30.468200Z" | ||
| } | ||
| }, | ||
| "outputs": [], | ||
| "source": [ | ||
| "log_folder_path = '/Users/jk1/Downloads/xgb_gs'\n", | ||
| "output_dir = '/Users/jk1/Downloads'" | ||
| ] | ||
| }, | ||
| { | ||
| "cell_type": "code", | ||
| "execution_count": null, | ||
| "id": "5df24c93e6096cfd", | ||
| "metadata": { | ||
| "ExecuteTime": { | ||
| "end_time": "2024-08-23T10:35:46.517467Z", | ||
| "start_time": "2024-08-23T10:35:46.374150Z" | ||
| } | ||
| }, | ||
| "outputs": [], | ||
| "source": [ | ||
| "gs_df = pd.DataFrame()\n", | ||
| "for root, dirs, files in os.walk(log_folder_path):\n", | ||
| " for file in files:\n", | ||
| " if file.endswith('.jsonl'):\n", | ||
| " temp_df = pd.read_json(os.path.join(root, file), \n", | ||
| " lines=True, dtype={'timestamp': 'object'}, convert_dates=False).drop(0)\n", | ||
| " # add file name as column\n", | ||
| " temp_df['file_name'] = file\n", | ||
| " gs_df = pd.concat([gs_df, temp_df], ignore_index=True)" | ||
| ] | ||
| }, | ||
| { | ||
| "cell_type": "code", | ||
| "execution_count": null, | ||
| "id": "ce6cba7b03680cb", | ||
| "metadata": { | ||
| "ExecuteTime": { | ||
| "end_time": "2024-08-23T10:35:49.821820Z", | ||
| "start_time": "2024-08-23T10:35:49.801767Z" | ||
| } | ||
| }, | ||
| "outputs": [], | ||
| "source": [ | ||
| "gs_df" | ||
| ] | ||
| }, | ||
| { | ||
| "cell_type": "code", | ||
| "execution_count": null, | ||
| "id": "b2e38efb0e502dd", | ||
| "metadata": { | ||
| "ExecuteTime": { | ||
| "end_time": "2024-08-23T10:36:20.053438Z", | ||
| "start_time": "2024-08-23T10:36:20.040408Z" | ||
| } | ||
| }, | ||
| "outputs": [], | ||
| "source": [ | ||
| "best_df = gs_df.sort_values('median_val_scores', ascending=False).head(1)\n", | ||
| "best_df" | ||
| ] | ||
| }, | ||
| { | ||
| "cell_type": "code", | ||
| "execution_count": null, | ||
| "id": "fba22c4b0b816d4c", | ||
| "metadata": {}, | ||
| "outputs": [], | ||
| "source": [] | ||
| } | ||
| ], | ||
| "metadata": { | ||
| "kernelspec": { | ||
| "display_name": "Python 3", | ||
| "language": "python", | ||
| "name": "python3" | ||
| }, | ||
| "language_info": { | ||
| "codemirror_mode": { | ||
| "name": "ipython", | ||
| "version": 2 | ||
| }, | ||
| "file_extension": ".py", | ||
| "mimetype": "text/x-python", | ||
| "name": "python", | ||
| "nbconvert_exporter": "python", | ||
| "pygments_lexer": "ipython2", | ||
| "version": "2.7.6" | ||
| } | ||
| }, | ||
| "nbformat": 4, | ||
| "nbformat_minor": 5 | ||
| } |