Jupiter Notebook中的GridSearchCV进度

Question

能否在Jupyter Notebook中查看GridSearchCV的进度？我正在python中运行此脚本：

param_grid = {'learning_rate': [0.05, 0.10, 0.15, 0.20, 0.25, 0.30] ,
'max_depth'        : [3, 4, 5, 6, 8, 10, 12, 15],
'min_child_weight' : [1, 3, 5, 7],
'gamma'            : [0.0, 0.1, 0.2 , 0.3, 0.4],
'colsample_bytree' : [0.3, 0.4, 0.5 , 0.7],
'verbose'          : [100] }

xgboost_reg = XGBRegressor()
grid_search = GridSearchCV(xgboost_reg, param_grid, cv=5, scoring='neg_mean_squared_error', return_train_score=True)
grid_search.fit(my_data, my_labels, verbose=False)

我只能在单元格的输出中看到一些警告。

Answer 1

您想要verbose参数：

grid_search = GridSearchCV(xgboost_reg, param_grid, cv=5, scoring='neg_mean_squared_error', return_train_score=True, verbose=2)
grid_search.fit(my_data, my_labels, verbose=False)

我从玩具数据中得到的例子：

Fitting 3 folds for each of 5 candidates, totalling 15 fits
[CV] C=0.1 ...........................................................
[CV] ............................................ C=0.1, total=   0.0s
[CV] C=0.1 ...........................................................
[CV] ............................................ C=0.1, total=   0.0s
[CV] C=0.1 ...........................................................
[CV] ............................................ C=0.1, total=   0.0s
[CV] C=0.5 ...........................................................
[CV] ............................................ C=0.5, total=   0.0s
[CV] C=0.5 ...........................................................
[CV] ............................................ C=0.5, total=   0.0s
[CV] C=0.5 ...........................................................
[CV] ............................................ C=0.5, total=   0.0s