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Adjusting gbdt.py's parameter (#660)
* Update gbdt.py * Update gbdt.py * Update gbdt.py
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@@ -14,11 +14,12 @@ from ...model.interpret.base import LightGBMFInt
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class LGBModel(ModelFT, LightGBMFInt):
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class LGBModel(ModelFT, LightGBMFInt):
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"""LightGBM Model"""
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"""LightGBM Model"""
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def __init__(self, loss="mse", **kwargs):
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def __init__(self, loss="mse", early_stopping_rounds=50, **kwargs):
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if loss not in {"mse", "binary"}:
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if loss not in {"mse", "binary"}:
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raise NotImplementedError
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raise NotImplementedError
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self.params = {"objective": loss, "verbosity": -1}
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self.params = {"objective": loss, "verbosity": -1}
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self.params.update(kwargs)
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self.params.update(kwargs)
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self.early_stopping_rounds = early_stopping_rounds
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self.model = None
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self.model = None
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def _prepare_data(self, dataset: DatasetH):
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def _prepare_data(self, dataset: DatasetH):
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@@ -44,7 +45,7 @@ class LGBModel(ModelFT, LightGBMFInt):
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self,
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self,
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dataset: DatasetH,
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dataset: DatasetH,
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num_boost_round=1000,
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num_boost_round=1000,
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early_stopping_rounds=50,
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early_stopping_rounds=None,
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verbose_eval=20,
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verbose_eval=20,
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evals_result=dict(),
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evals_result=dict(),
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**kwargs
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**kwargs
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@@ -56,7 +57,9 @@ class LGBModel(ModelFT, LightGBMFInt):
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num_boost_round=num_boost_round,
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num_boost_round=num_boost_round,
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valid_sets=[dtrain, dvalid],
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valid_sets=[dtrain, dvalid],
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valid_names=["train", "valid"],
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valid_names=["train", "valid"],
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early_stopping_rounds=early_stopping_rounds,
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early_stopping_rounds=(
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self.early_stopping_rounds if early_stopping_rounds is None else early_stopping_rounds
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),
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verbose_eval=verbose_eval,
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verbose_eval=verbose_eval,
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evals_result=evals_result,
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evals_result=evals_result,
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**kwargs
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**kwargs
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