App Behaviour Analysis
This repo consists of the App Behaviour Analysis Case Study
Problem
To predict which users will not subscribe to the paid membership of the Application involved, with the help of various features provided for each user, so that greater marketing efforts can go into trying to convert those users to Paid Users.
Model Used
The case study utilises Logistic Regression Model from the Scikit Learn Library, which is evaluated using K-Fold Cross Validation & Grid Search
Visualisation of the data
The following plot (Matplotlib Subplots) shows Histograms of 7 of the Features from the entire Dataset
Correlation with User Enrolled
The following plot (Pandas Bar Plot) shows a measure of the Correlation of the above features, with the Response Variable (Enrollment of the User)
