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r/MachineLearning - [D] Tips on improving random forest predictive accuracy when # of features is really low?

#artificialintelligenceSep-10-2019, 06:13:24 GMT

Normally when I do RF projects I use some sort of feature selection method to choose which features to use. Then I fit the RF model onto those features. Then to test accuracy / related metrics I use cross validation, confusion matrices, etc. However in this case I only have two given features. I don't want to just literally run a RF model on those two features as my whole entire project. I'm thinking gradient boosting is what I should learn?

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