Hello everyone,

I’m studying ICT at the University and i’m currently working on a project involving transport data: the dataset me and my colleagues gathered involves territorial information (demographic-economic), points of interest (bars, restaurants, universities…) and some mobility data (users’ trips with origin and destination). The goal of the project is to develop a ML algorithm to classify the trip purpose of the users (based on all these inputs, try to classify if it’s a work trip, entertainment trip, going to eat ecc…).

My question is, if possible, if it is a good idea to use a semi-supervised algorithm that tries to label the unlabelled data (since we don’t have any validation on the mobility data) using some rules to establish some obvious labels. If not, are there any better methods?