Overview In the linear regression prediction, we want to find a hypothesis function to predict the future outcome. The method in supervised learning is by using loads of training data sets and a learning algorithm to let the result of the hypothesis function close to the real value as possible as we can. ...

Basic Method When learning the eigenvalue and eigenvector, we are commonly given an equation at the beginning $$ AX = \lambda X \tag{1} $$ Where A is the matrix X is the eigenvector $\lambda$ is the eigenvalue Take an example Q: Find the eigenvalues and eigenvectors of the matrix $$ A = \begin{bmatrix} 1&1&-2\ -1&2&1\ 0&1&-1 \end{bmatrix} $$ A: To get the answer, firstly apply the equation (1) : $$ AX = \lambda X \tag{1} $$ ...