[Solved] Machine learning, Splunk, feature importance in Random Forest Regressor or Random Forest Classifier?
I have a new fuel battery ML project. There are procedures
1000 to manufacture new fuel battery. What I am trying to do at this stage is to check which procedure/feature is the most influential/effect on final battery quality: (
Capacity, resistence, voltage).
splunk ML toolbo splunk-training x, I could see there is and
RandomForestRegressoralgorithms. Which algorithm I shall use so that I could utilize the model's method
feature importance to point out the most effect/influential procedure/feature to battery quality.