Know the distance from each point to the origin of the coordinate system (Pythagorean theorem), where:
There are two main ideas in PCA derivation:
They are two characteristics of unified existence,
We seek the sum of maximum variance and minimum error.
There are n pieces of d-dimensional data:
Suppose a group of points use PCA to reduce the dimension of data.
That is, find the eigenvalues and eigenvectors of covariance matrix:
Among them,
Among them,
Correlation coefficient: use, to represent the relationship between random variables x and y.
1. dimensionality reduction algorithm of principal component analysis-principle and implementation
2. How to explain what PCA is in an easy-to-understand way?
3. Mathematical principle and derivation of principal component analysis.
4. The PCA algorithm is deduced in detail.