5190332c创建于 2024年6月26日历史提交
文件最后提交记录最后更新时间
Adjust rolling api (#1594) * Intermediate version * Fix yaml template & Successfully run rolling * Be compatible with benchmark * Get same results with previous linear model * Black formatting * Update black * Update the placeholder mechanism * Update CI * Update CI * Upgrade Black * Fix CI and simplify code * Fix CI * Move the data processing caching mechanism into utils. * Adjusting DDG-DA * Organize import2 年前
Add some misc features. (#1816) * Normal mod * Black linting * Linting1 年前
Adjust rolling api (#1594) * Intermediate version * Fix yaml template & Successfully run rolling * Be compatible with benchmark * Get same results with previous linear model * Black formatting * Update black * Update the placeholder mechanism * Update CI * Update CI * Upgrade Black * Fix CI and simplify code * Fix CI * Move the data processing caching mechanism into utils. * Adjusting DDG-DA * Organize import2 年前
Adjust rolling api (#1594) * Intermediate version * Fix yaml template & Successfully run rolling * Be compatible with benchmark * Get same results with previous linear model * Black formatting * Update black * Update the placeholder mechanism * Update CI * Update CI * Upgrade Black * Fix CI and simplify code * Fix CI * Move the data processing caching mechanism into utils. * Adjusting DDG-DA * Organize import2 年前
README.md

Introduction

This is the framework of periodically Rolling Retrain (RR) forecasting models. RR adapts to market dynamics by utilizing the up-to-date data periodically.

Run the Code

Users can try RR by running the following command:

    python rolling_benchmark.py run

The default forecasting models are Linear. Users can choose other forecasting models by changing the model_type parameter. For example, users can try LightGBM forecasting models by running the following command:

    python rolling_benchmark.py --conf_path=workflow_config_lightgbm_Alpha158.yaml run