I have observed that when I significantly reduce the dimensionality of my data that the silhouette score drastically increases. I have reduced the dimensionality so that only 10% of the variance is retained.
With no dimensionality reduction, I get on average silhouette scores ~0. With dimensionality reduction, only keeping 10% variance, I get a score of ~.78.
Based on the silhouette score, is the data actually better clustered in this low dimensionality, or have I manipulated the data too much for this score to be reliable?