Simple machine learning algorithm for spatiotemporal sequence regression prediction?
Currently, there are many solutions for spatiotemporal sequence prediction problems, such as ConvLSTM, SocialLSTM, etc.However, in my personal opinion, these algorithms are very difficult to understand and not user-friendly for beginners or non-professionals in machine learning.I have no background in machine learning and do not want to delve into those algorithms. I just want to use the scenario I want.Personally, I feel that this problem is simplified and should not be difficult for an algorithm.The simplified problem is as follows: There is a plane with 9 points on it, each representing a data point that is known. A set of nine data points represents the state at one time, and the data for n time steps (t-n…t-1, t) is known. I want to predict the state for future time steps.Please design some simpler and more understandable algorithms to solve this problem. The simpler the algorithm, the better.v2-1e1174b9695da1bfd957469786506d57_r890×328 32.6 KB