I have been given a task with a real transaction dataset. The task is to predict something using either logistic regression or simple binary classification.
The columns are as follow:
- Transaction ID
- Quantity purchased
- Product name
- Coupon code
- Transaction Date
- City (where transaction was made)
- Delivery fee (if any)
- Total amount spent
I am having a rough time figuring out what to predict using regression or classification given only these columns.
i.e: Given a full row how much is the total spent... etc
In other words I need help deciding what will be the label of my dataset and what would be the reason behind choosing that label.