The question is
- Why PCA needs to consider perpendicular distance?
- Why PCA needs to cater for maximal variance?
For Question (1), from this link:
while PCA is to minimize the perpendicular distance from the model and the PCA model line,e.g.,
Why PCA needs to consider perpendicular distance?
For Question (2), from this link, it mentions that the objective of PCA wants to achieve two objectives:
- The minimum error
- The maximum variance
My second question is why we need maximum variance? Does this objective have anything to do with the previous question on perpendicular distance?