Analyzing transactions of a retailer to predict promotional items.
The dataset has previous five years purchase transactions of customers. Predictive analysis is done by applying machine learning algorithms to find the most frequent item sets purchased.
Aprioir Algorithms : To generate associatin rules and find the most frequent item sets. Support Vector Machines : To predict the month of the year in which the sales of a particular item is maximum.
Shiny (Library in R) is used to display the results. Shiny Dashboard: https://niranjanrshiny.shinyapps.io/Prediction_App/