[scikit-learn] interpretation of manifold.MDS results

[Bill Ross]

I have a set of photos and a set of metrics for assigning distances 
between them. I am out to find the dimensionality of (space needed to 
embed) each set of distances, out of curiosity and to inform my use of 
the metrics in forming the character of an AI.

It was suggested that manifold.MDS could help, and it looked perfect for 
a toy case I wrote. However, with actual data I found that the stress_  
term doesn't go to 0 when the number of components reaches the number of 
points:

http://stackoverflow.com/questions/37855596/calculate-the-spatial-dimension-of-a-graph

I'm not sure if this question has achieved visibility, since I added the 
scikit-learn tag after it was created. I'd appreciate any discussion of 
the meaning of the value in the limit for stress_, and whether a 
meaningful dimensionality measure can be derived.

Thanks,
Bill