Eigenvectors, Principal Component, Dimensionality Reduction, Data Science, Unsupervised Learning.
point and random line) gets bigger c (distance between origin and projected point ) gets smaller. So, if we increase c we will be able to reduce the distance between the random line and point a. PCA finds the best fit line by maximizing the distances from the origin to the projected point. 3.Let