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Add early stopping to double ensemble model, add example (#1375)

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* Add early stopping to double ensemble model, add example

* Fix lint error
This commit is contained in:
Di
2022-11-28 14:02:44 +08:00
committed by GitHub
parent c4ee9ff882
commit 7e5bab599a
2 changed files with 104 additions and 2 deletions
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11
qlib/contrib/model/double_ensemble.py
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@@ -30,6 +30,7 @@ class DEnsembleModel(Model, FeatureInt):
sample_ratios=None,
sub_weights=None,
epochs=100,
early_stopping_rounds=None,
**kwargs
):
self.base_model = base_model # "gbm" or "mlp", specifically, we use lgbm for "gbm"
@@ -59,6 +60,7 @@ class DEnsembleModel(Model, FeatureInt):
self.params = {"objective": loss}
self.params.update(kwargs)
self.loss = loss
self.early_stopping_rounds = early_stopping_rounds
def fit(self, dataset: DatasetH):
df_train, df_valid = dataset.prepare(
@@ -103,14 +105,19 @@ class DEnsembleModel(Model, FeatureInt):
def train_submodel(self, df_train, df_valid, weights, features):
dtrain, dvalid = self._prepare_data_gbm(df_train, df_valid, weights, features)
evals_result = dict()
callbacks = [lgb.log_evaluation(20), lgb.record_evaluation(evals_result)]
if self.early_stopping_rounds:
callbacks.append(lgb.early_stopping(self.early_stopping_rounds))
self.logger.info("Training with early_stopping...")
model = lgb.train(
self.params,
dtrain,
num_boost_round=self.epochs,
valid_sets=[dtrain, dvalid],
valid_names=["train", "valid"],
verbose_eval=20,
evals_result=evals_result,
callbacks=callbacks,
)
evals_result["train"] = list(evals_result["train"].values())[0]
evals_result["valid"] = list(evals_result["valid"].values())[0]