I am following this tutorials: https://www.datacamp.com/community/tutorials/random-forests-classifier-python on using Scikit-learn with random forests. However, the current code only shows the test accuracy whereas I want to know the training accuracy as well since may dataset is very small.

The code to get the test accuracy is:

from sklearn import metrics
print("Accuracy:", metrics.accuracy_score(y_test, y_pred))

How would I modify this to get the training accuracy?

CodePudding user response：

You can get the training set predictions as

y_train_pred = clf.predict(X_train) 

where clf is your fitted RandomForestClassifier. After that you can use

metrics.accuracy_score(y_train, y_train_pred) 

to calculate the training accuracy. Alternatively, you can use

clf.score(X_train, y_train)

which should give you the same result.