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depress warning with pandas option_context (#1524)
Co-authored-by: Cadenza-Li <362237642@qq.com>
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@@ -136,7 +136,7 @@ If you want to contribute your new models, you can follow the steps below.
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- `README.md`: a brief introduction to your models
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- `workflow_config_<model name>_<dataset>.yaml`: a configuration which can read by `qrun`. You are encouraged to run your model in all datasets.
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3. You can integrate your model as a module [in this folder](https://github.com/microsoft/qlib/tree/main/qlib/contrib/model).
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4. Please update your results in the above **Benchmark Tables**, e.g. [Alpha360](#alpha158-dataset), [Alpha158](#alpha158-dataset)(the values of each metric are the mean and std calculated based on **20 Runs** with different random seeds. You can accomplish the above operations through the automated [script](https://github.com/microsoft/qlib/blob/main/examples/run_all_model.py#LL286C22-L286C22) provided by Qlib, and get the final result in the .md file. if you don't have enough computational resource, you can ask for help in the PR).
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4. Please update your results in the above **Benchmark Tables**, e.g. [Alpha360](#alpha158-dataset), [Alpha158](#alpha158-dataset)(the values of each metric are the mean and std calculated based on **20 Runs** with different random seeds. You can accomplish the above operations through the automated [script](https://github.com/microsoft/qlib/blob/main/examples/run_all_model.py) provided by Qlib, and get the final result in the .md file. if you don't have enough computational resource, you can ask for help in the PR).
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5. Update the info in the index page in the [news list](https://github.com/microsoft/qlib#newspaper-whats-new----sparkling_heart) and [model list](https://github.com/microsoft/qlib#quant-model-paper-zoo).
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Finally, you can send PR for review. ([here is an example](https://github.com/microsoft/qlib/pull/1040))
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