Walmart Trip Type Classification ML Project
I used a Walmart trip type dataset provided from a Kaggle competition. Along with 4 groupmates, we tested several several classification algorithms to find the best results.
Classification involves predicting discrete class labels for unlabeled data given information on the data. The data we are working with is information from individuals’ shopping trips at Walmart. The data is broken down into 7 observations, one of which is the trip type which tells us what type of shopping trip this customer was on, visit number which organizes the data into individual shopping trips, weekday that the trip was done on, UPC number of the item purchased, department of purchase and the fineline number which is a number that Walmart made helping us specify the items purchased. Given certain data such as what weekday it is, what department it was in, and what the UPC was, our goal is to be able to predict what type of shopping trip someone was on based off of a couple pieces of data.
A jupyter notebook containing our whole thought process and approach to this problem can be found in the link above the photo.
