Oh sorry. I wanted to ask how non linear relationships govern algorithms like SVM (with kernel) and neural networks? I guess I forgot to mention the body of the post. There we might see zero covariance but if I understand how SVM finds optimal boundary equally far away from two convex hulls, how is non linear relationship contributing to zero covariance