Is it possible to see the progress of GridSearchCV in a Jupyter Notebook? I’m running this script in python:
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)
I can see only some warnings in the output of the cell.
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Answer
You want the verbose parameter:
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)
An example of what I got on toy data:
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