Hello Prajna_450:
In data mining, the number of inputs is often large, The usual correlation/covariance matrix is on the order of the square of the number of inputs, so it can quickly become so large that interpreting it can become tedious. However, if you do want to see it, then one method is to use the Principal Components node with the Print Eigenvalue Source property changed from No to Yes.
A more manageable approach might be to use the StatExplore node to compute standard univariate statistics, to compute standard bivariate statistics by class target and class segment, and to compute correlation statistics for interval variables by interval targets.
Variance Inflation Factor (VIF) is displayed for interval targets by the HP Regression node.
Thank you for your interest!
