# Which machine learning approach can be used to predict a univariate value?

I have a stream of data coming in like below (random numbers 0-9)

7, 7, 0, 0, 8, 9, 2, 7, 3, 8, 2, 8, 5, 7, 0, 8, 7, 8, 5, 3, 2, 6, 1, 9, 5, 7, 5, 3, 4, 9, 1, 3, 5, 5, 0, 7, 7, 5, 2, 8, 8, 7, 5, 5, 5, 2, 9, 7, 2, 1, 0, 0, 5, 7, 1, 4, 2, 7, 8, 8, 5, 2, 7, 5, 7, 1, 7, 2, 0, 5, 7, 5, 2, 6, 3, 6, 3, 6, 1, 9, 1, 9, 7, 2, 3, 9, 8, 8, 4, 9, 8, 2, 5, 3, 4, 0, 3, 1, 0, 7, 2, 3, 8, 7, 5, 7, 3, 6, 0, 3, 3, 3, 6, 3, 1, 3, 0, 6, 9, 8, 0, 1, 4, 4, 9, 9, 3, 7, 4, 1, 0, 5, 0, 6, 8, 8, 8, 1, 7, 6

Ask: is to Predict the next numbers(at least 3-10).

Which approach would be helpful in getting through this problem?

• Hidden Markov Models: Treating your discrete numbers as states, you can use HMMs to predict the next state (next number) by looking at the last or the $$n$$ last states.