**Instructions**


- Run the telcoChurn-main.R to drive the R demo
- Run the telcoChurn-modelComparison.R to compare different algorithms that we tried to build churn models



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**Description**

- **telcoChurn-setUp.R** - Setting up relevant R packages
- **telcoChurn-evaluate.R** - Defining pre-functions for model evaluation 
- **telcoChurn-dataExploration.R** - Creating a Shiny application to explore and visualize the data
- **telcoChurn-dataPreparation.R** - Defining functions to do data pre-processing and spliting in order to generate suitable training and testing data sets
- **telcoChurn-trainModel.R** - Defining a function to train the telco churn model with rxDForest algorithm
- **telcoChurn-main.R** - Main R file driving the demo execution
- **telcoChurn-modelComparison.R** - R file to build and compare different tree-based classification models, including CRAN R algorithms - randomForest and xgboost, RevoScaleR algorithms – rxDForest and rxBTrees

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