How does one deal with a feature vector that can vary in size?
Let's say per object, I calculate 4 features. In order to solve a certain regression problem, I may have 1, 2, or more of these objects (no more than 10). Thus, the feature vector is 4*N in length. How is this normally addressed?
The objects represent physical objects (e.g. other people) w.r.t. an observer. For a time slice, an object can be placed laterally, longitudinally, have some speed and some heading (4 features). Trying to solve: where should a person feel most comfortable. In some cases there is only 1 object, but there can be 2 or more.
Disclaimer: I have limited knowledge on ML approaches. I had classes in college years ago and took Andrew Ng's ML course online as a refresher but otherwise not up to speed. A starting place to look is appreciated.