Summary STA2005S: PCA

Principal Component Analysis
Aim : PCA is a
dimensionality reduction technique ,



that identifies new
meaningful variables in dataset


Overview : PCA creates new variables ,
called principal components ,

that linear combination's of the variables
are
original
L
v
s



PCA Variables Each component explains PCA components arranged
uncorrelated percentage of in order of
are a
decreasing
variation in Oct dataset variance explained