Catogorising strings into random versus non-random

[Mark Lawrence]

On 21/12/2015 16:49, Ian Kelly wrote:
> On Mon, Dec 21, 2015 at 9:40 AM, duncan smith <duncan at invalid.invalid> wrote:
>> Finite state machine / transition matrix. Learn from some English text
>> source. Then process your strings by lower casing, replacing underscores
>> with spaces, removing trailing numeric characters etc. Base your score
>> on something like the mean transition probability. I'd expect to see two
>> pretty well separated groups of scores.
>
> Sounds like a case for a Hidden Markov Model.
>

In which case https://pypi.python.org/pypi/Markov/0.1 would seem to be a 
starting point.

-- 
My fellow Pythonistas, ask not what our language can do for you, ask
what you can do for our language.

Mark Lawrence