Monty Python Markov Chain

Description

This model is an implementation of Markov Chain that uses dialogs from Monty Python Flying Circus [Kaggle] to predict or generate the skit sentences.

The reasonability of the generated sentences is, however, arguable...

The model works in two modes.

Predictive mode

The model predicts the subsequent words by means of greatest p_value based on the original dialogs. Unfortunately it has a chance of falling into infinite loops.

Generative mode

The model predicts the subsequent words by means of uniform random value compared with thresholds generated from the sorted cumulative p_values.

Example

input:

"Hello"
"Hello" 
"The weather"
"Ah, yes... The weather"
"Indeed"
"Do"
"No"
"Goodbye"
"Goodbye" 

output:

- Hello, sir.
- Hello?
- The weather.
- Ah, yes... the weather.
- Indeed i take a passer by ann haydon jones the sordid details of the start with it is the arts'.
- Do you say, he's cured.
- No.
- Goodbye.
- Goodbye betty muriel sartre.

Conclusion

The model is too simple and thus useless.