I have a set of data objects defined by 20 dimensions rated from 1 to 10 with no decimal. There is no hierarchy between dimensions.
I am able to calculate the similarity between objects but I do not want to compare a new object to the whole set of existing objects every time a new one is inserted. Machine learning seems to be the right solution for this task. I ve read some interesting stuff basing my research on this https://en.wikipedia.org/wiki/Similarity_learning
Do you have an idea on which machine learning algorithm would suit the best to my needs ?