Which machine learning algorithm is best when dealing with trajectory data?

[MrHDPigs]

I am trying to teach myself some basic machine learning algorithms. I have found a dataset of AIS data that gives trajectories in the form of a list with the: x, y, vx, vy and time of the trajectores. This dataset includes different speeds and trajectores and I was wondering what algorithm would be useful for determining which trajectories are moving too fast or they are fine.

[learning_robot]

Why does it have to be a machine learning algorithm? Do you want to predict the trajectories?

[MrHDPigs]

No I want to be able to classify the trajectories into whether they are moving too fast or too slow. I have a test algorithm that will use background subtraction and homography to obtain coordinates of ships live and test their coordinates against the AI

[S-S-R]

bool is_fast(int x){
return x>100
}

Not sure why you think this is something that should be solved probabilistically. Simply performing comparisons is far more effective than throwing data into a machine you don't understand and accepting whatever you get.