title: Cluster Size is too big after BIRCH clustering
body: <p>I have a data of 2,4million row and about 56 variables. I was doing sampling of 10000 data and do PCA into 10 dimensions</p>
  
  <p>Then I use BIRCH clustering as k-means and hierarchical were showing bad silhoutte coefficient. Scikit says that the usecase of BIRCH is large dataset and data reduction</p>
  
  <p>As the result, I get 4 clusters with Silhoutte coefficient of 0,4 (-1 is the worst, 1 is the best) which I think it is good enough. The problem is, the first cluster size is too big, it get 94% of all data, meanwhile the other clusters only get 6%</p>
  
  <p>So my questions are ; Do PCA and Sampling affect the BIRCH clustering result? And what can be done to cluster that dominate the size?</p>
  
  <p>I am thinking of either do re-clustering to the 94% or just accept the fact that 94% of my data is really have the same cluster.
  Thanks</p>