Customer Churn project for a telecom firm. The project aims to predict the possibility of a customer to churn by using methods of Data Analysis and Machine Learning with sound accuracy and justifies its result by showing the expected cost-benefit from following their recommendations.
The code folder contains four .R files and the Dataset. Make sure to change the R working directory to the project folder
=> All information is sourced in 'MAIN.R' => You can run everything from this fie. => Functions are available in 'Functions.R' => Visulations in 'Visualisations.R' => 'ML_Models.R' has all four models.
NOTE that...
- The working directory must be changed to the code folder to be able to source the additional functions
- All modelling is done by using R language (ver 3.5.1) and run on RStudio (ver 1.1.463).
- Several CRAN libraries and packages were used in the project
VERY IMPORTANT LINK (Pivate) - Apologies, but will not be able to share https://drive.google.com/file/d/1tBC9TQxrxi0umVJz3fG9xuOwErga-GrE/view?usp=sharing