I have a multiclass problem (3 classes) that looks to predict if someone will buy a product, neutral or not. I have initial features of in-app activity data such as likes, share, bookmark, share, clicks, etc. (all of them were collected before the purchase date).
Do I still need to do Temporal Train-Validation-Test split or is a random one in scikit-learn enough? If yes, is Temporal splitting always the way to go for tabular data classification problems?