打印 CatBoost 超参数
Print CatBoost hyperparameters
如何在训练模型后打印 CatBoost 超参数?
在sklearn
中,我们可以只打印模型对象,它将显示所有参数,但在catboost
中,它只打印对象的引用:<catboost.core.CatBoostRegressor object at 0x7fd441e5f6d8>
.
from catboost import CatBoostRegressor
# Initialize data
train_data = [[1, 4, 5, 6],
[4, 5, 6, 7],
[30, 40, 50, 60]]
eval_data = [[2, 4, 6, 8],
[1, 4, 50, 60]]
train_labels = [10, 20, 30]
# Initialize CatBoostRegressor
model = CatBoostRegressor(iterations=2,
learning_rate=1,
depth=2)
# Fit model
model.fit(train_data, train_labels)
# Get predictions
preds = model.predict(eval_data)
print (model)
print(model.get_params()) 应该做
使用print(model.get_all_params())
打印所有默认参数。
如何在训练模型后打印 CatBoost 超参数?
在sklearn
中,我们可以只打印模型对象,它将显示所有参数,但在catboost
中,它只打印对象的引用:<catboost.core.CatBoostRegressor object at 0x7fd441e5f6d8>
.
from catboost import CatBoostRegressor
# Initialize data
train_data = [[1, 4, 5, 6],
[4, 5, 6, 7],
[30, 40, 50, 60]]
eval_data = [[2, 4, 6, 8],
[1, 4, 50, 60]]
train_labels = [10, 20, 30]
# Initialize CatBoostRegressor
model = CatBoostRegressor(iterations=2,
learning_rate=1,
depth=2)
# Fit model
model.fit(train_data, train_labels)
# Get predictions
preds = model.predict(eval_data)
print (model)
print(model.get_params()) 应该做
使用print(model.get_all_params())
打印所有默认参数。