Truncated SVD
- PCA Principal Component Analysis (PCA) is the subject of a previous post of mine, so I will only summarize it here.
- Data reduction via PCA is accomplished by linearly transforming the data into a new coordinate system where (most of) the variation in the data can be described with fewer dimensions than the initial data.
- Without getting into the details, this involves an eigen-decomposition of the covariance matrix.
Unverified
- PCA Principal Component Analysis (PCA) is the subject of a previous post of mine, so I will only summarize it here.
- Data reduction via PCA is accomplished by linearly transforming the data into a new coordinate system where (most of) the variation in the data can be described with fewer dimensions than the initial data.
- Without getting into the details, this involves an eigen-decomposition of the covariance matrix.
Sources: Brashandplucky