Take the 2-minute tour ×  I'm trying to detect how well an input
vector fits a given cluster centre. I can find the best match
quite easily (the centre with the minimum euclidean distance to
the input vector is the best), however, I now need to work how
good a match that is.  To do this I need to find the spread
(standard deviation?) of the vectors which build up the
centroid, then see if the distance from my input vector to the
centre is less than the spread. If it's more than the spread
than I should be able to say that I have no clusters to fit it
(given that the best doesn't fit the input vector well).  I'm
not sure how to find the spread per cluster. I have all the
centre vectors, and all the training vectors are labelled with
their closest cluster, I just can't quite fathom exactly what I
need to do to get the spread.  I hope that's clear? If not I'll
try to reword it! TIA Ian  share|improve this question add
comment  2 Answers  up vote 3 down vote accepted  Use the
distance function and calculate the d