mirror of
https://github.com/microsoft/qlib.git
synced 2026-07-04 11:30:57 +08:00
fix model when using single feature
This commit is contained in:
@@ -61,7 +61,7 @@ class CatBoostModel(Model):
|
||||
if self.model is None:
|
||||
raise ValueError("model is not fitted yet!")
|
||||
x_test = dataset.prepare("test", col_set="feature")
|
||||
return pd.Series(self.model.predict(np.squeeze(x_test.values)), index=x_test.index)
|
||||
return pd.Series(self.model.predict(x_test.values), index=x_test.index)
|
||||
|
||||
|
||||
if __name__ == "__main__":
|
||||
|
||||
@@ -16,7 +16,7 @@ class LGBModel(ModelFT):
|
||||
def __init__(self, loss="mse", **kwargs):
|
||||
if loss not in {"mse", "binary"}:
|
||||
raise NotImplementedError
|
||||
self.params = {"objective": loss}
|
||||
self.params = {"objective": loss, 'verbosity': -1}
|
||||
self.params.update(kwargs)
|
||||
self.model = None
|
||||
|
||||
@@ -65,7 +65,7 @@ class LGBModel(ModelFT):
|
||||
if self.model is None:
|
||||
raise ValueError("model is not fitted yet!")
|
||||
x_test = dataset.prepare("test", col_set="feature", data_key=DataHandlerLP.DK_I)
|
||||
return pd.Series(self.model.predict(np.squeeze(x_test.values)), index=x_test.index)
|
||||
return pd.Series(self.model.predict(x_test.values), index=x_test.index)
|
||||
|
||||
def finetune(self, dataset: DatasetH, num_boost_round=10, verbose_eval=20):
|
||||
"""
|
||||
|
||||
@@ -61,4 +61,4 @@ class XGBModel(Model):
|
||||
if self.model is None:
|
||||
raise ValueError("model is not fitted yet!")
|
||||
x_test = dataset.prepare("test", col_set="feature")
|
||||
return pd.Series(self.model.predict(xgb.DMatrix(np.squeeze(x_test.values))), index=x_test.index)
|
||||
return pd.Series(self.model.predict(xgb.DMatrix(x_test.values)), index=x_test.index)
|
||||
|
||||
Reference in New Issue
Block a user