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Update R and workflow

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This commit is contained in:
Jactus
2020-11-17 22:05:18 +08:00
parent a8b46dd41d
commit 64ed43b791
20 changed files with 481 additions and 376 deletions
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59
qlib/contrib/model/gbdt.py
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@@ -12,6 +12,7 @@ from ...data.dataset.handler import DataHandlerLP
class LGBModel(ModelFT):
"""LightGBM Model"""
def __init__(self, loss="mse", **kwargs):
if loss not in {"mse", "binary"}:
raise NotImplementedError
@@ -20,9 +21,9 @@ class LGBModel(ModelFT):
self.model = None
def _prepare_data(self, dataset: DatasetH):
df_train, df_valid = dataset.prepare(["train", "valid"],
col_set=["feature", "label"],
data_key=DataHandlerLP.DK_L)
df_train, df_valid = dataset.prepare(
["train", "valid"], col_set=["feature", "label"], data_key=DataHandlerLP.DK_L
)
x_train, y_train = df_train["feature"], df_train["label"]
x_valid, y_valid = df_valid["feature"], df_valid["label"]
@@ -36,23 +37,27 @@ class LGBModel(ModelFT):
dvalid = lgb.Dataset(x_valid.values, label=y_valid)
return dtrain, dvalid
def fit(self,
dataset: DatasetH,
num_boost_round=1000,
early_stopping_rounds=50,
verbose_eval=20,
evals_result=dict(),
**kwargs):
def fit(
self,
dataset: DatasetH,
num_boost_round=1000,
early_stopping_rounds=50,
verbose_eval=20,
evals_result=dict(),
**kwargs
):
dtrain, dvalid = self._prepare_data(dataset)
self.model = lgb.train(self.params,
dtrain,
num_boost_round=num_boost_round,
valid_sets=[dtrain, dvalid],
valid_names=["train", "valid"],
early_stopping_rounds=early_stopping_rounds,
verbose_eval=verbose_eval,
evals_result=evals_result,
**kwargs)
self.model = lgb.train(
self.params,
dtrain,
num_boost_round=num_boost_round,
valid_sets=[dtrain, dvalid],
valid_names=["train", "valid"],
early_stopping_rounds=early_stopping_rounds,
verbose_eval=verbose_eval,
evals_result=evals_result,
**kwargs
)
evals_result["train"] = list(evals_result["train"].values())[0]
evals_result["valid"] = list(evals_result["valid"].values())[0]
@@ -76,10 +81,12 @@ class LGBModel(ModelFT):
verbose level
"""
dtrain, _ = self._prepare_data(dataset)
self.model = lgb.train(self.params,
dtrain,
num_boost_round=num_boost_round,
init_model=self.model,
valid_sets=[dtrain],
valid_names=["train"],
verbose_eval=verbose_eval)
self.model = lgb.train(
self.params,
dtrain,
num_boost_round=num_boost_round,
init_model=self.model,
valid_sets=[dtrain],
valid_names=["train"],
verbose_eval=verbose_eval,
)