Does having a positive or negative correlation between features being clustered affect the agglomerative clustering result?
I have three columns in my dataset, and I'm trying to figure out if I should cluster on all three features or use only a subset.
The Pearson correlation coefficients are:
X & Z --> -0.07, p=0.14 X & Y --> -0.08, p=0.08 Z & Y --> 0.68, p<0.001
The Variance Inflation Factor is:
variables VIF Y 2.816716 X 3.552227 Z 6.232414
Should I choose X and Y because p-value > 0.05: The correlation is not statistically significant? Just looking at the Variance Inflation Factor and Pearson Correlation analysis enough to determine which features should be chosen for clustering?