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Update all baseline models.

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This commit is contained in:
lwwang1995
2020-11-27 22:30:05 +08:00
parent 7952d79932
commit bebce24a7c
17 changed files with 282 additions and 856 deletions
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12
qlib/contrib/model/xgboost.py
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@@ -38,14 +38,18 @@ class XGBModel(Model):
):
df_train, df_valid = dataset.prepare(
["train", "valid"], col_set=["feature", "label"], data_key=DataHandlerLP.DK_L
["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"]
# Lightgbm need 1D array as its label
if y_train.values.ndim == 2 and y_train.values.shape[1] == 1:
y_train_1d, y_valid_1d = np.squeeze(y_train.values), np.squeeze(y_valid.values)
y_train_1d, y_valid_1d = np.squeeze(y_train.values), np.squeeze(
y_valid.values
)
else:
raise ValueError("XGBoost doesn't support multi-label training")
@@ -68,4 +72,6 @@ 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(x_test.values)), index=x_test.index)
return pd.Series(
self.model.predict(xgb.DMatrix(x_test.values)), index=x_test.index
)