XGBoosterror：参数的值超过界限

我正在训练 XGBoost 模型，并使用 randomizedSearchCV 进行超参数调整。我将参数分布指定为：

from xgboost import XGBRegressor

# Define a xgboost regression model
model = XGBRegressor()

params = {
      "colsample_bytree": uniform(0.1, 0.2), # fraction of cols to sample
      "gamma": uniform(0, 0.3), # min loss reduction required for next split
      "learning_rate": uniform(0.02, 0.3), # default 0.1 
      "n_estimators": randint(100, 150), # default 100
      "subsample": uniform(0.8, 0.75) # % of rows to use in training sample
}

r = RandomizedSearchCV(model, param_distributions=params, n_iter=100, 
scoring="neg_mean_absolute_error", cv=3, n_jobs=1)

即使我为 subsample 指定的范围较低的范围，我也会得到以下错误

raise XGBoostError(py_str(_LIB.XGBGetLastError()))
   xgboost.core.XGBoostError: value 1.10671 for Parameter subsample exceed bound [0,1]

  warnings.warn("Estimator fit failed. The score on this train-test"

知道为什么会这样吗？