I have some data that I want to classify. As an initial measure, I did PCA for the data and I saw two distinct clusters of my data. However, when standardizing the data, the two clusters disappear. What can this mean? that the data is easily separated by individual variance or mean of the features? if that is the case, how can I do classification?
Edit: Following the commenters' requests, I am adding an image of my clustered data. Since the PCA is of higher dimension than 3, it is hard to see why classification succeeds from this image. Also, the colors are the TRUE results, not estimated ones.