I’m advancing a bit more in my models and started to think that GP might be suitable for my current objective.
There is a strong (r2: +0.95) linear/quadratic relationship between velocity~load for exercises like the squat, bench press & deadlift.
I have a dataset where each row is a session and it contains columns for each measurement in that session, i.e. each measurement pair (velocity, load) + exercise, is a feature. I also have a label column that contains the max load lifted in each session.
My objective is to train a model with N measurements per observation and estimate what the max load would be.
I’m limited by a rather small number of observations, think < 100 in total, ~30 per exercise.
Is GP a good way to go or should I look into something else?