Random Forest Classifier decision path visualisation

Asked Sep 25 '17 at 07:03

Active Sep 25 '17 at 07:03

Viewed 1,241 times

# training forest
clf_random_Forest = ensemble.RandomForestClassifier(n_estimators=8, 
min_samples_split=300)
clf_random_Forest.fit(training_data,training_label)
# method in use
clf_random_Forest.decision_path(test_data)

I read the documentation and found this method, but its description is not very informative, to put it mildly. did anyone come across this method? can I visualize it, if so how? Here I found only one question about this method, but in the answers I suggested visualizing individual trees.

asked Sep 25 '17 at 07:03

AndrewP

You can checkout this answer : https://stackoverflow.com/questions/40155128/plot-trees-for-a-random-forest-in-python-with-scikit-learn – sourabh1024 Sep 25 '17 at 07:29
2

i don't need trees visualization i need decision_path() – AndrewP Sep 25 '17 at 08:10

Random Forest Classifier decision path visualisation

0 Answers0