Pick centers in KMeans++ with a probability proportional to their distance^2, instead of simple distance, to previous centers
Apply to KMeansIndex KMeanspp the same modification as in HierarchicalClusteringIndex
As some processed distances are already ^2, use template to select whether or not we have to ^2 in KMeanspp
Move templates in dist.h in order to share them between KMeansIndex and HierarchicalClusteringIndex classes.
perf report: summary.py: added custom --regressions map
Merge pull request #2016 from pemmanuelviel:kmeansppSquareDist
Merge pull request #2544 from alalek:perf_report_regressions