A random forest model outputs the following importance values. How do I interpert them for feature selection? If it's the mean decreased accuracy does that mean that by removing them from the model the accuracy should increase?
Topic feature-importances random-forest
Category Data Science
I'm not sure which software you're using so I don't know the details, but generally it's simple: the highest values indicate the features which contribute the most to the target.
In particular, the mean decrease in accuracy shows how much the accuracy decreases when removing this feature. Thus again a high value (e.g. emotionality in your example) indicates an important feature for predicting the target.
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