From eb1e1b9ef22fe58720dfa71f01b812eecaf32b87 Mon Sep 17 00:00:00 2001 From: yzlin Date: Wed, 7 Feb 2024 21:54:40 +0800 Subject: [PATCH] mv examples --- examples/ci/{data_analysis.py => data_visualization.py} | 0 examples/{ => ci}/email_summary.py | 0 examples/ci/machine_learning.py | 0 examples/{ => ci}/ml_engineer_with_tools.py | 6 +++--- 4 files changed, 3 insertions(+), 3 deletions(-) rename examples/ci/{data_analysis.py => data_visualization.py} (100%) rename examples/{ => ci}/email_summary.py (100%) create mode 100644 examples/ci/machine_learning.py rename examples/{ => ci}/ml_engineer_with_tools.py (74%) diff --git a/examples/ci/data_analysis.py b/examples/ci/data_visualization.py similarity index 100% rename from examples/ci/data_analysis.py rename to examples/ci/data_visualization.py diff --git a/examples/email_summary.py b/examples/ci/email_summary.py similarity index 100% rename from examples/email_summary.py rename to examples/ci/email_summary.py diff --git a/examples/ci/machine_learning.py b/examples/ci/machine_learning.py new file mode 100644 index 000000000..e69de29bb diff --git a/examples/ml_engineer_with_tools.py b/examples/ci/ml_engineer_with_tools.py similarity index 74% rename from examples/ml_engineer_with_tools.py rename to examples/ci/ml_engineer_with_tools.py index 1c90f2946..1c73a1dd0 100644 --- a/examples/ml_engineer_with_tools.py +++ b/examples/ci/ml_engineer_with_tools.py @@ -9,8 +9,8 @@ async def main(requirement: str, auto_run: bool = True, use_tools: bool = True): if __name__ == "__main__": - data_path = "your_path_to_icr/icr-identify-age-related-conditions" # 替换 'your_path_to_icr' 为实际数据存放的路径 - train_path = f"{data_path}/your_train_data.csv" # 替换 'your_train_data.csv' 为你的训练数据文件名 - eval_path = f"{data_path}/your_eval_data.csv" # 替换 'your_eval_data.csv' 为你的评估数据文件名 + data_path = "your_path_to_icr/icr-identify-age-related-conditions" + train_path = f"{data_path}/your_train_data.csv" + eval_path = f"{data_path}/your_eval_data.csv" requirement = f"This is a medical dataset with over fifty anonymized health characteristics linked to three age-related conditions. Your goal is to predict whether a subject has or has not been diagnosed with one of these conditions.The target column is Class. Perform data analysis, data preprocessing, feature engineering, and modeling to predict the target. Report f1 score on the eval data. Train data path: {train_path}, eval data path:{eval_path}." asyncio.run(main(requirement))