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Add a new method to benchmarks: DoubleEnsemble #286

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merged 12 commits into from
Mar 2, 2021

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meng-ustc
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Description

Motivation and Context

How Has This Been Tested?

  • Pass the test by running: pytest qlib/tests/test_all_pipeline.py under upper directory of qlib.
  • If you are adding a new feature, test on your own test scripts.

Screenshots of Test Results (if appropriate):

  1. Pipeline test:
  2. Your own tests:

Types of changes

  • Fix bugs
  • Add new feature
  • Update documentation

@ghost
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ghost commented Feb 24, 2021

CLA assistant check
All CLA requirements met.

@you-n-g you-n-g requested a review from Derek-Wds February 24, 2021 08:14
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LGTM! 😄

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Screenshot from 2021-02-23 17-04-39

@@ -232,6 +232,7 @@ Here is a list of models built on `Qlib`.
- [SFM based on pytorch (Liheng Zhang, et al. 2017)](qlib/contrib/model/pytorch_sfm.py)
- [TFT based on tensorflow (Bryan Lim, et al. 2019)](examples/benchmarks/TFT/tft.py)
- [TabNet based on pytorch (Sercan O. Arik, et al. 2019)](qlib/contrib/model/pytorch_tabnet.py)
- [DoubleEnsemble based on LightGBM (Chuheng Zhang, et al. 2020)](qlib/contrib/model/double_ensemble.py)
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Could you update your model results here ?
https://github.com/microsoft/qlib/tree/main/examples/benchmarks

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The results are up to date now.

**kwargs
):
self.base = base # "gbm" or "mlp", specifically, we use lgbm for "gbm"
self.k = k
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Please give more details about the parameters.
Give it a full name at least

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OK. The new names are "base_model" and "num_models".

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you-n-g commented Mar 2, 2021

@meng-ustc
It looks great. Thanks for your great efforts :)

@you-n-g you-n-g merged commit 0bcaab3 into microsoft:main Mar 2, 2021
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3 participants