

Ask HN: Bayesian FTW - Pamar

Reading this HN entry (https:&#x2F;&#x2F;news.ycombinator.com&#x2F;item?id=9780677) has rekindled my interest in Bayesian logic.
My main introduction to the topic was through original Stanford AI MOOC.
I managed to get decent scores on all the Bayesian-related stuff, but I cannot say I really internalize the ideas.<p>What I am looking for is something that could help me making practical use of Bayes in my day-to-day life (professional and&#x2F;or personal).<p>So I am basically thinking of:<p>- books or articles detailing practical examples of how to apply Bayesian models to day-to-day choices (if these covered debug and testing activities it would be a big plus)
- an easy-to-use app (desktop or tablet&#x2F;smartphone) to build and play with Bayesian networks models.<p>Of course, if you have anything else to suggest along the same lines, please do.
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duncanawoods
I honestly don't believe Bayes is that relevant to day to day decision making
but I'm keen to see a counter-argument (I have some but I don't find them
convincing yet).

I see Bayes as a method to solve certain classes of problem but the key
challenge in everyday decisions is more like a design problem i.e. to define
what the problem is. Once you have defined "what would be a good outcome of
this decision" sufficiently, the answer rarely requires statistical methods.
The common sources of error in a decision are in its definition e.g. omitting
a requirement that is later revealed as essential.

For example, if you are analysing drug studies, Bayes is obviously relevant
but for something more common place such as choosing a software tool, the main
challenge is to understand what your goals are so that you can identify the
criteria by which to judge the tools and the trade-offs you are willing to
accept.

The biggest steps to improving decision quality appear to be process related
e.g. using prototypes to explore options before making a larger commitment.
Such acts are so effective because they reveal information that lets you
_improve your goals_ rather than just clarifying the quality of an option.

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Pamar
Well, I wouldn't be surprised if the only practical benefit in building a
Bayesian Network model ended up being that "that you had to think long and
hard at what the various inputs are and how they should be linked".

I am curious if there is any kind of resource that would help me to
confidently add Bayes to my normal decision-making toolchest.

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duncanawoods
Yep, I can see the value as a thinking tool. There are tools like
[http://www.bayesia.com/](http://www.bayesia.com/) and
[http://www.hugin.com/](http://www.hugin.com/) but they are enterprise pricey
and I find them very clunky.

I'd love to know how your ideal tool might work. Do you mind if I drop you an
email (from your profile info)?

I'm working on a decision making tool to let you quickly describe reasoning
with simple bullet point lists. It aims to be as quick as a making a rough
note so that with just a few different types of bullet, you can create belief
networks and computable decision models.

The tool is intended for a general audience so it currently uses simple
weighted evidence. If you can tell me how you would like to work with
probabilities then you might get the tool you want :)

~~~
Pamar
Sorry, seen this only now... please feel free to write directly, thanks.

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jrgnsd
I find that having a bayes classifier handy can help a lot with categorizing
documents or text. I manually keep track of my bank accounts using a
spreadsheet, and I started using a classifier to automatically categorize the
transaction. It's quite a time saver.

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Pamar
Can you explain what you use as categorization elements?

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jrgnsd
You train your own set by posting the document and the classification /
category to the service. The training set is then used to calculate the prior
probabilities needed by Bayes theorem. Once you have a proper training set,
you can post a document to the service and it will return a list of probable
categories from the training set.

Your set might look something like this:

Category - Document

negative - I don't like ice cream

positive - That's an awesome idea

neutral - The wind is blowing today

positive - We won!

You'll get a categorization of either positive, negative or neutral.

~~~
Pamar
Yes, well - I understand the general theory, but I don't understand how it
applies to managing your bank account.

I do manage my bank account, but I don't see any need for an "classifier":
when I input (or check) a supermarket bill I don't need much help in setting
it to "GROCERIES". Basically anything that gets into my accounting files it's
either something I know already what is about, or else something I need to
investigate (e.g.: a speed ticket from a foreign country, routed to my credit
card by the car rental company).

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roller
I've had this one stacked up on my reading list for a while:
[http://camdavidsonpilon.github.io/Probabilistic-
Programming-...](http://camdavidsonpilon.github.io/Probabilistic-Programming-
and-Bayesian-Methods-for-Hackers/)

It details how to use the PyMC library via iPython notebooks. I'm not sure if
iPython qualifies as an easy to use app though.

