[evolution] recapturing singletons in similarity programm
The aim of this functionality is to find new clusters inside the set of singletons produced by similarity program. A further evolution will consist to study a fusion methods of clusters which will be the recall stategy of our clustering method, by using multisets (one cluster = one multiset).
First step : copying singletons in a dedicated directory. This function should be optional for debugging and testing new ncd.
Second step : including a "-enroll" parameter in similarity program which will compute new clusters from all singletons. In this case, similarity should work on existing distance matrix. This relaunch of similarity will use same parameters than in first launch.
Third step : complete integration of this functionality (docker).