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Construct A New Tree from Random Forest Result
My dataset has 130 features, and I use one feature a time to train a classifier with Random Forest. Some of these 130 generated classifiers give good results. However, when I use two features in Random Forest(RF) training, the performance is not that good. So I would like to use several of the 1-feature-trained RF classifier to build up a tree classifier by giving the results of the 1-feature-trained classifiers different weights. I would like to know what operators can I use in RapidMiner to implement this. Do I have to work in the code level?