Train a markov model for string generation. This module provides some wrapper functionality around the markov
module so that you can do word generation. Sentence generation using markov models is fairly straight forward by using
lists of Strings as training data. Just like how the core String module makes some character operations easier this
section helps to wrap List Char operations into a more simpler String interface. This module contains only the
operations that benefit from simplification not covered by the core library. This sections also serves as a good
template on how to extend the markov package for use in your own data.
Create an empty markov string object.
Train the markov model on a single string. This trains the model to store the transition probabilities of all the letters within the string as well as the probabilities to start with the first character and end with the last character.
Train the model on a sample of data or an entire corpus.
Encode the markov string model into a json object.
Decode a json object into a markov string model.
A type alias for a markov graph which is used on determining probabilities of character transitions in words.