

Small Introduction to Markov Chains - tantalum
http://blog.circuitsofimagination.com/2015/02/15/Markov-Chains.html

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mts_
I like the visualization vicapow did on Markov chains a while ago as well.

"Markov chains explained visually": [http://setosa.io/blog/2014/07/26/markov-
chains/](http://setosa.io/blog/2014/07/26/markov-chains/)

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sswaner
That is a great intro. Thanks for putting it together. If you were to continue
this to a Part #2, I would be interested in seeing the approach for
determining if something was "abnormal". Is it considered abnormal to add a
node to the chain, or to add a transition? Is detecting abnormal behavior more
complicated than detecting new nodes or transitions?

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tantalum
Abnormal really means that it has a probability less than some threshold. So
you might have a transition that has a probability of less then 0.1, depending
on your situation, you might consider that abnormal even thought that
transition does exist. Also a non existent transition would be considered
"abnormal" because the probability is 0 in your model.

I've been thinking about doing a part 2 with text analysis and a cool use case
would be to detect "abnormal" text from an author because he/she uses strings
of words that have a low probability in the rest of their text.

Hope this helps and I'm glad you like the post.

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sswaner
Thanks for the response. Yours is the clearest intro to Markov Chains that I
have found.

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taterbase
Awesome intro! I've used Markov Chain libraries before but never took the time
to try and understand them. This makes a lot of sense.

Are there different or more efficient probability calculations that can be
done other than the provided algorithm? It seems somewhat simple.

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tantalum
Yes there are more complex probabilities that you can calculate. For example
you can calculate the probability of reaching some state that is one or more
transitions away given a starting state. You can find more info on some of
other calculations you can do on Wikipedia.

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jszymborski
damn, that's some tiny <pre> font-size.

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crncosta
Agree.

