我正在使用 XGBoost 进行销售预测。我需要一个自定义目标函数，因为预测值取决于商品的销售价格。我正在努力将销售价格输入到标签和预测旁边的损失函数中。这是我的方法：
def monetary_value_objective(predt: np.ndarray, dtrain: Union[xgb.DMatrix, np.ndarray]) -> Tuple[np.ndarray, np.ndarray]:
"""
predt = model prediction
dtrain = labels
Currently, dtrain is a numpy array.
"""
y = dtrain
mask1 = predt <= y # Predict too few
mask2 = predt > y # Predict too much
price = train[0]["salesPrice"]
grad = price **2 * (predt - y)
# Gradient is negative if prediction is too low, and positive if it is too high
# Here scale it (0.72 = 0.6**2 * 2)
grad[mask1] = 2 * grad[mask1]
grad[mask2] = 0.72 * grad[mask2]
hess = np.empty_like(grad)
hess[mask1] = 2 * price[mask1]**2
hess[mask2] = 0.72 * price[mask2]**2
grad = -grad
return grad, hess
超参数调整时出现以下错误：
[09:11:35] WARNING: /workspace/src/objective/regression_obj.cu:152: reg:linear is now deprecated in favor of reg:squarederror.
0%| | 0/1 [00:00<?, ?it/s, best loss: ?]
---------------------------------------------------------------------------
IndexError Traceback (most recent call last)
<ipython-input-34-2c64dc1b5a76> in <module>()
1 # set runtime environment to GPU at: Runtime -> Change runtime type
----> 2 trials, best_hyperparams = hyperpara_tuning(para_space)
3 final_xgb_model = trials.best_trial['result']['model']
4 assert final_xgb_model is not None, "Oooops there is no model created :O "
5
17 frames
/usr/local/lib/python3.6/dist-packages/pandas/core/indexers.py in check_array_indexer(array, indexer)
399 if len(indexer) != len(array):
400 raise IndexError(
--> 401 f"Boolean index has wrong length: "
402 f"{len(indexer)} instead of {len(array)}"
403 )
IndexError: Boolean index has wrong length: 1 instead of 136019
有谁知道如何在目标函数中使用销售价格？这可能吗？
谢谢！