I am trying to plot the categories I have obtained via DBSCAN on a 30-dimensional dataset 12 categories, and I want to visualize them in a 2d plot.
My procedure was to reduce that 30-dimensional dataset to a 2-dimensional one using PCA, and then color the categories using the ones obtained before with the 30-dim dataset.
The inconsistency I am facing is that when plotting, the 'clusters' don't seem to match the logic of density of DBSCAN, which is the fact that leads me to think that my process is in the wrong order, but I dont wanna reduce dimensions and then cluster, and then go back to 30 dimensions again.
Is there any right order to follow?
2) But if I use DBSCAN on the 30-dim dataset and then reduce the dimensions and plot using the original categories is:
In both results I don't get the same results with the Nearest Neighbors knee that is used to choose an optimal epsilon in DBSCAN.