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Add a new method to benchmarks: DoubleEnsemble #286
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@@ -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".
@meng-ustc |
Description
Motivation and Context
How Has This Been Tested?
pytest qlib/tests/test_all_pipeline.py
under upper directory ofqlib
.Screenshots of Test Results (if appropriate):
Types of changes