6
$\begingroup$

I am getting:

AttributeError: 'RandomForestClassifier' object has no attribute 'oob_score_'. But I can see the attribute oob_score_ in sklearn random forest classifier documentation.

param = [10,15,20,25,30, 40]  
# empty list that will hold cv scores
cv_scores = []
# perform 10-fold cross validation
for i in tqdm(param):
    clf = RandomForestClassifier(n_estimators = i, max_depth = None,bootstrap = True, oob_score = True)
    scores = clf.oob_score_
    cv_scores.append(scores)

ERROR

AttributeError                            Traceback (most recent call last)
<ipython-input-37-d6c9c54f299e> in <module>()
     15 for i in tqdm(param):
     16     clf = RandomForestClassifier(n_estimators = i, max_depth = None,bootstrap = True, oob_score = True)
---> 17     scores = clf.oob_score_
     18     cv_scores.append(scores)
     19 

AttributeError: 'RandomForestClassifier' object has no attribute 'oob_score_'
Improve this question
$\endgroup$
3
  • 4
    $\begingroup$ You have not used fit method. How can it return oob_score_? $\endgroup$ Commented Aug 28, 2018 at 10:59
  • $\begingroup$ Thanks! It worked.. oob_score_ is for Generalization accuracy but wat if i want to check the performance metric other than accuracy on cross validation data? $\endgroup$ Commented Aug 28, 2018 at 11:05
  • $\begingroup$ @HarikaM Depends on your task. Choose that metric which best describes the output of your task. $\endgroup$ Commented Aug 30, 2018 at 5:41

1 Answer 1

Reset to default
2
$\begingroup$

This kaggle guide explains Random Forest.

Setting warm_start to True might give you a solution to your problem. The default value is False.

Improve this answer
$\endgroup$

Your Answer

By clicking “Post Your Answer”, you agree to our terms of service and acknowledge you have read our privacy policy.

Start asking to get answers

Find the answer to your question by asking.

Ask question

Explore related questions

See similar questions with these tags.