GitHub - BrahmajitMohapatra/Customer-Churn-Data-Analysis-using-R: I have worked on Customer Churn dataset to find out which model is more efficient for the same. I did descriptive analysis of the data,used summary function to understand the data, implemented data cleaning, remove NA values from the dataset. Did some data manipulations, gained some knowledge about the rows and columns, attributes about the data. I have also perfomed Data Visualization using ggplot2 library. I have ploted barplot, scatterplot, and boxplot on data available.Also implemented Linear Regression and Multiple Linear Regression models, in which I compared the models based on RMSE (Root Mean Square Error) and found that Linear Regression is more efficient and best suit for the Customer Churn Dataset.

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I have worked on Customer Churn dataset to find out which model is more efficient for the same. I did descriptive analysis of the data,used summary function to understand the data, implemented data cleaning, remove NA values from the dataset. Did some data manipulations, gained some knowledge about the rows and columns, attributes about the data…