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Chuck Berry turned 90-years old today and announced his first album in 38 years. Berry’s last studio album was 1979’s Rock It. The new album, simply titled Chuck, comes out in 2017 and is dedicated to his wife of 68 years Themetta Berry. His band which includes some of hisContinue Reading
This is code that accompanies a book chapter on customer churn that I have written for the German dpunkt Verlag. The book is in German and will probably appear in February: https://www.dpunkt.de/buecher/13208/9783864906107-data-science.html. The code you find below can be used to recreate all figures and analyses from this book chapter. Because the content is exclusively for the book, my descriptions around the code had to be minimal. But I’m sure, you can get the gist, even without the book. ;-) Inspiration & Sources Thank you to the following people for providing excellent code examples about customer churn: Matt Dancho: http://www.business-science.io/business/2017/11/28/customer_churn_analysis_keras.html JJ Allaire: https://github.com/rstudio/keras-customer-churn Susan Li: https://towardsdatascience.com/predict-customer-churn-with-r-9e62357d47b4 John Sullivan: https://jtsulliv.github.io/churn-eda/ Setup All analyses are done in R using RStudio. For detailed session information including R version, operating system and package versions, see the sessionInfo() output at the end of this document. All figures are produced with ggplot2. Libraries # Load libraries library(tidyverse) # for tidy data analysis library(readr) # for fast reading of input files library(caret) # for convenient splitting library(mice) # mice package for Multivariate Imputation by Chained Equations (MICE) library(keras) # for neural nets library(lime) # for explaining neural nets library(rsample) # for splitting training and test data library(recipes) # for preprocessing library(yardstick) # for evaluation library(ggthemes) # for additional plotting themes library(corrplot) # for correlation theme_set(theme_minimal()) # Install Keras if you have not installed it before # follow instructions if you haven't installed TensorFlow install_keras() Data preparation The dataset The Telco Customer Churn data set is the same one that Matt Dancho used in his post (see above). It was downloaded from IBM Watson churn_data_raw
