Simple Markov Chain implementation. The model generates the next token according to the input token based on hardcoded input data.

build & run : guess how

Hardcoded data: {1,2,3,4,5,6,7,8,7,8,7,8,7,8,2,3,2,3,2,3,2,3}

Hardcoded data computed statistical model:

1 | stats:

2 : 1 : 1

2 | stats:

3 : 5 : 1

3 | stats:

2 : 3 : 0.75

4 : 1 : 0.25

4 | stats:

5 : 1 : 1

5 | stats:

6 : 1 : 1

6 | stats:

7 : 1 : 1

7 | stats:

8 : 4 : 1

8 | stats:

2 : 1 : 0.25

7 : 3 : 0.75

Generated output:

2,3,2,3,2,3,2,3,2,3,2,3,2,3,2,3,2,3,2,3,4,5,6,7,8,2,3,2,3,2,3,2,3,2,3,2,3,2,3,2,3,2,3,2,3,2,3,2,3,2,3,4,5,6,7,8,7,8,7,8,7,8,7,8,7,8,7,8,7,8,7,8,2,3,2,3,2,3,2,3,2,3,2,3,4,5,6,7,8,7,8,7,8,7,8,7,8,7,8,7,8,7,8,7

As we can see, the output [token --> next token] sequences frequencies are valid according to the gathered data statistics.