Random Forest Classifier in RapidMiner
In this tutorial, I explain how to build a Random Forest Classifier for the multi-class classification problem. The IRIS data set is utilized. Preprocessing, selecting the target variable, and splitting the data into a training and test set are done. A Random Forest Classifier is then built using the training set and its performance on both the training set and test set are measured. The results are further explained.
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