Developing a design support system for the exterior form of running shoes using partial least squares and neural networks

It is observed that PLS is superior to PCA in performance on dimension reduction because it considers the Y information variable and encompasses causal relationships when converting the original variable X into a latent variable, while PCA has a limited ability in reducing dimensions when causal relationships between the variables are disregarded.