title: Distance and metrics between datasets
body: <p>I have almost 30 different data-sets. Each of them contain a different number of variables and the dimension is around 46. </p>
  
  <p>I'm trying to measure the distance between these data-sets, rather than the distance between the items within each data set themselves. My proposal is to find the mean for each data-set and the to use euclidean or mahalanobis distance to find the linkage and build my structure. </p>
  
  <p>I already know the number of clusters, as it is defined by the number of data sets. I just need to find the distance between my data sets. </p>
  
  <p>Is the way I'm doing this good enough or should I find a metric other than the average which better represents each data set? Do these distance functions fit the measurement or not? Is it necessary to do any normalization or dissimilarity calculation?  </p>