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* make the prediction update more friendly * Update test_storage.py * LabelUpdater * Update test_storage.py * Update test_storage.py * Update test_storage.py * Update test_storage.py * Update setup.py * Update workflow_config_lightgbm_Alpha158.yaml * Update workflow_config_lightgbm_Alpha158.yaml * Update workflow_config_lightgbm_Alpha158.yaml * Update workflow_config_lightgbm_Alpha158.yaml * Update workflow_config_lightgbm_Alpha158.yaml * Update setup.py * Update setup.py * test CI only * test CI only * Update workflow_config_lightgbm_Alpha158.yaml * Update setup.py * fix "Segmentation fault" in macos * Update test.yml github action no longer supported ubuntu-16.04 * Update api.rst update doc with new_lable * Update api.rst Co-authored-by: Wangwuyi123 <51237097+Wangwuyi123@users.noreply.github.com> Co-authored-by: Pengrong Zhu <zhu.pengrong@foxmail.com>
Requirements
Here is the minimal hardware requirements to run the workflow_by_code example.
- Memory: 16G
- Free Disk: 5G
NOTE
The results will slightly vary on different OSs(the variance of annualized return will be less than 2%).
The evaluation results in the README.md page are from Linux OS.