This package helps to build & evaluate Classification Models such as CART & Random Forest.
This is the only package which has functions that can help to create, optimize and evaluate the model at a single place and you get a list as an output which can be used further in different functions as input for further analysis.
It saves a lot of time to run specific functions for CART & Random Forest and then measure the performance of those models on different parameters.
This package helps in evaluating the Models created on multiple Evaluation Parameters like Confusion Matrix, Accuracy, Recall, Sphericity, AUC, KS, Gini, Concordance, Discordance, Pairs & Ties.