Reputation: 384
I am trying to implement decision tree classifier using GridSearchCV. After implementation i tried to to access cv_results_.mean_train_score but i am getting key error.
tuned_parameters = [{'max_depth': [1, 5, 10, 25, 50, 75, 100, 150, 250, 500, 750, 1000],
'min_samples_split' : [5, 10, 25, 50, 75, 150, 250, 500]}]
cv_timeSeries = TimeSeriesSplit(n_splits=4).split(X_train)
base_estimator = DecisionTreeClassifier(class_weight='balanced')
gsearch_cv = GridSearchCV(estimator=base_estimator,
param_grid=tuned_parameters,
cv=cv_timeSeries,
scoring='roc_auc',
n_jobs=-1)
gsearch_cv.fit(X_train, y_train)
When i am trying to access all the keys of gsearch_cv, i am unable to find dict key mean_train_score.
Upvotes: 2
Views: 8197
Reputation: 11
Try the following change:
gsearch_cv = GridSearchCV(estimator=base_estimator,
param_grid=tuned_parameters,
cv=cv_timeSeries,
scoring='roc_auc',
return_train_score=True,
n_jobs=-1,
return_train_score=True)
Upvotes: -1
Reputation: 452
Could you please post the code that generates the error?
mean_train_score is a key of cv_results_ so to get his values you shall:
gsearch_cv = GridSearchCV(estimator=base_estimator,
param_grid=tuned_parameters,
cv=cv_timeSeries,
scoring='roc_auc',
return_train_score=True,
n_jobs=-1)
gsearch_cv.fit(X_train, y_train)
gsearch_cv.cv_results_['mean_train_score']
You can find a complete example on the sklearn page https://scikit-learn.org/stable/modules/generated/sklearn.model_selection.GridSearchCV.html
Upvotes: 3
Reputation: 359
add the parameter following parameter in GridSearchCV
GridSearchCV(return_train_score=True)
Upvotes: 11