I have a project that's aimed to predict the amount of occupants at my local gym given the date and weather.
I have two datasets, occupants on a given hour and weather on a given hour. My process is that I combine these two datasets, and using Occupants as the target. However, when I implement a regression algorithm I can only reach a prediction score of 57%.
I'd love any advice on how to modify my solution to achieve better predictions?