{"metadata":{"kernelspec":{"language":"python","display_name":"Python 3","name":"python3"},"language_info":{"name":"python","version":"3.10.14","mimetype":"text/x-python","codemirror_mode":{"name":"ipython","version":3},"pygments_lexer":"ipython3","nbconvert_exporter":"python","file_extension":".py"},"kaggle":{"accelerator":"none","dataSources":[{"sourceId":88400,"databundleVersionId":10121331,"sourceType":"competition"}],"dockerImageVersionId":30786,"isInternetEnabled":true,"language":"python","sourceType":"notebook","isGpuEnabled":false}},"nbformat_minor":4,"nbformat":4,"cells":[{"cell_type":"code","source":"# This Python 3 environment comes with many helpful analytics libraries installed\n# It is defined by the kaggle/python Docker image: https://github.com/kaggle/docker-python\n# For example, here's several helpful packages to load\n\nimport numpy as np # linear algebra\nimport pandas as pd # data processing, CSV file I/O (e.g. pd.read_csv)\n\n# Input data files are available in the read-only \"../input/\" directory\n# For example, running this (by clicking run or pressing Shift+Enter) will list all files under the input directory\n\nimport os\nfor dirname, _, filenames in os.walk('/kaggle/input'):\n    for filename in filenames:\n        print(os.path.join(dirname, filename))\n\n# You can write up to 20GB to the current directory (/kaggle/working/) that gets preserved as output when you create a version using \"Save & Run All\" \n# You can also write temporary files to /kaggle/temp/, but they won't be saved outside of the current session","metadata":{"_uuid":"8f2839f25d086af736a60e9eeb907d3b93b6e0e5","_cell_guid":"b1076dfc-b9ad-4769-8c92-a6c4dae69d19","trusted":true,"execution":{"iopub.status.busy":"2024-11-11T07:27:46.974362Z","iopub.execute_input":"2024-11-11T07:27:46.974784Z","iopub.status.idle":"2024-11-11T07:27:46.982725Z","shell.execute_reply.started":"2024-11-11T07:27:46.974741Z","shell.execute_reply":"2024-11-11T07:27:46.981664Z"}},"outputs":[],"execution_count":null},{"cell_type":"code","source":"train = pd.read_csv(\"/kaggle/input/aiffel-ds-3-credit-card-fraud-detection/train.csv\") \ntest = pd.read_csv(\"/kaggle/input/aiffel-ds-3-credit-card-fraud-detection/test.csv\")\nsubmission = pd.read_csv(\"/kaggle/input/aiffel-ds-3-credit-card-fraud-detection/sample_submission.csv\")","metadata":{"trusted":true,"execution":{"iopub.status.busy":"2024-11-11T07:27:49.034141Z","iopub.execute_input":"2024-11-11T07:27:49.034681Z","iopub.status.idle":"2024-11-11T07:27:51.279674Z","shell.execute_reply.started":"2024-11-11T07:27:49.034629Z","shell.execute_reply":"2024-11-11T07:27:51.278573Z"}},"outputs":[],"execution_count":null},{"cell_type":"code","source":"from sklearn.ensemble import RandomForestClassifier\n\n\n# 입력 특성과 타겟 변수 분리\nX_train = train.drop(['id', 'Class'], axis=1)\ny_train = train['Class']\n\nX_test = test.drop(['id'], axis=1)","metadata":{"trusted":true,"execution":{"iopub.status.busy":"2024-11-11T07:27:52.650464Z","iopub.execute_input":"2024-11-11T07:27:52.651421Z","iopub.status.idle":"2024-11-11T07:27:52.678525Z","shell.execute_reply.started":"2024-11-11T07:27:52.651378Z","shell.execute_reply":"2024-11-11T07:27:52.677647Z"}},"outputs":[],"execution_count":null},{"cell_type":"code","source":"# 로지스틱 회귀 모델 학습\nmodel = RandomForestClassifier()\nmodel.fit(X_train, y_train)","metadata":{"trusted":true,"execution":{"iopub.status.busy":"2024-11-11T07:27:54.251005Z","iopub.execute_input":"2024-11-11T07:27:54.251814Z","iopub.status.idle":"2024-11-11T07:30:35.775500Z","shell.execute_reply.started":"2024-11-11T07:27:54.251769Z","shell.execute_reply":"2024-11-11T07:30:35.774423Z"}},"outputs":[],"execution_count":null},{"cell_type":"code","source":"# 테스트 데이터에 대한 예측\ny_pred = model.predict(X_test)","metadata":{"trusted":true,"execution":{"iopub.status.busy":"2024-11-11T07:30:39.369173Z","iopub.execute_input":"2024-11-11T07:30:39.369572Z","iopub.status.idle":"2024-11-11T07:30:40.481007Z","shell.execute_reply.started":"2024-11-11T07:30:39.369531Z","shell.execute_reply":"2024-11-11T07:30:40.479896Z"}},"outputs":[],"execution_count":null},{"cell_type":"code","source":"# 제출 파일 생성\nsubmission = pd.DataFrame({'id': test['id'], 'Class': y_pred})\nsubmission.to_csv('submission.csv', index=False)","metadata":{"trusted":true,"execution":{"iopub.status.busy":"2024-11-11T07:30:44.764109Z","iopub.execute_input":"2024-11-11T07:30:44.764881Z","iopub.status.idle":"2024-11-11T07:30:44.864696Z","shell.execute_reply.started":"2024-11-11T07:30:44.764825Z","shell.execute_reply":"2024-11-11T07:30:44.863802Z"}},"outputs":[],"execution_count":null},{"cell_type":"code","source":"submission","metadata":{"trusted":true,"execution":{"iopub.status.busy":"2024-11-11T07:30:48.360760Z","iopub.execute_input":"2024-11-11T07:30:48.361186Z","iopub.status.idle":"2024-11-11T07:30:48.377156Z","shell.execute_reply.started":"2024-11-11T07:30:48.361145Z","shell.execute_reply":"2024-11-11T07:30:48.376150Z"}},"outputs":[],"execution_count":null},{"cell_type":"code","source":"","metadata":{"trusted":true},"outputs":[],"execution_count":null}]}