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be4646b4b7
* 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 import
32 lines
939 B
Python
32 lines
939 B
Python
# Copyright (c) Microsoft Corporation.
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# Licensed under the MIT License.
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import qlib
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from qlib.constant import REG_CN
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from qlib.utils import init_instance_by_config
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from qlib.tests.data import GetData
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from qlib.tests.config import CSI300_GBDT_TASK
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if __name__ == "__main__":
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# use default data
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provider_uri = "~/.qlib/qlib_data/cn_data" # target_dir
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GetData().qlib_data(target_dir=provider_uri, region=REG_CN, exists_skip=True)
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qlib.init(provider_uri=provider_uri, region=REG_CN)
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###################################
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# train model
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###################################
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# model initialization
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model = init_instance_by_config(CSI300_GBDT_TASK["model"])
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dataset = init_instance_by_config(CSI300_GBDT_TASK["dataset"])
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model.fit(dataset)
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# get model feature importance
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feature_importance = model.get_feature_importance()
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print("feature importance:")
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print(feature_importance)
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