I have a lot to activity tracker data for many different users along almost two years. Some users have only few records, while others have more. I would like to show a user how their data (steps, bmi, calories) compare to the data of similar users. Additionally the user would also get an idea of its progress as they jump from one group to another. However defining similar users is a difficult task, it depends for example, on the individual metabolism, activity level, amount of calories ingested, and probably many others.Does anyone have an idea which machine learning algorithm would be suitable in this case? Ive read that it is possible to project data from similar users using  Collaborative Filtering algorithms, and I have an idea to use it for my problem. What is your opinion?
Find similar users from activity tracker data
machine learning;clustering