Machine Learning, Artificial Intelligence, Data Science.
one. Any Markov matrix A has an eigenvalue of 1 and the absolute value of other non-one eigenvalues to be smaller than one. This behavior is very important. In our example, For a Markov matrix, we can choose the eigenvector for λ=1 to have elements sum up to 1.0. So vectors v0 can be decomposed