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Interest in a Common Lisp library for Bayesian Network inference?
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Luke Hope
Jul 12, 2012, 10:55:55 PM7/12/12
to
Hi all,
I've been hanging on to some code I developed about 5-6 years ago when I was in academia. I'm wondering if I should open source it.
It is a native pure lisp Bayesian Network inference engine. It has two types of compilation:
1. 'Standard' Join Tree such as implemented by e.g. Netica circa 2008.
2. Arithmetic Circuits, which was a new research direction at the time.
The arithmetic circuit module is able to compile a Bayesian Network to lisp, C or Java standalone source code. That is, you don't need any libraries at all to perform probabilistic inference.
Just curious.
I've been hanging on to some code I developed about 5-6 years ago when I was in academia. I'm wondering if I should open source it.
It is a native pure lisp Bayesian Network inference engine. It has two types of compilation:
1. 'Standard' Join Tree such as implemented by e.g. Netica circa 2008.
2. Arithmetic Circuits, which was a new research direction at the time.
The arithmetic circuit module is able to compile a Bayesian Network to lisp, C or Java standalone source code. That is, you don't need any libraries at all to perform probabilistic inference.
Just curious.
Pascal J. Bourguignon
Jul 13, 2012, 4:30:42 AM7/13/12
to
- documentation.
- asdf file.
- distributed with quicklisp.
--
__Pascal Bourguignon__ http://www.informatimago.com/
A bad day in () is better than a good day in {}.
ddd
Jul 13, 2012, 6:09:55 AM7/13/12
to
gathering dust on your hard disk (also better for the hard disk :)
ccc31807
Jul 13, 2012, 4:04:40 PM7/13/12
to
On Jul 12, 10:55 pm, Luke Hope <rukubi...@gmail.com> wrote:
> Hi all,
>
> I've been hanging on to some code I developed about 5-6 years ago when I was in academia. I'm wondering if I should open source it.
Bayesian data analysis seems fashionable now, with new books and
> Hi all,
>
> I've been hanging on to some code I developed about 5-6 years ago when I was in academia. I'm wondering if I should open source it.
courses, in particular, Kruschke's book with R, and the recent courses
at SEE, Udacity, and Coursera. I'm a data munger by trade, not a
statistician, nevertheless I've audited a couple of these courses and
have bought a couple of books on R, including Kruschke's book.
Much of my job consists of reporting data, and I've gravitated to R
because of its very strong graphical capabilities. I can't use it for
data analysis but I certainly do use it to produce all sorts of
graphical output. A picture really is worth a thousand words.
I would ABSOLUTELY release your code to the public. I think it's a
GREAT idea, and I would encourage you to do so.
That said, I would make sure that you include sample data sets and a
detailed cookbook using your module. If you want to appeal to the
largest possible audience, assume that curiosity rather than need will
attract users. I wouldn't think a tutorial on Bayes' rule is
appropriate, people can find plenty in the public domain in this
regard. I do think a goodly number of examples showing how to use your
code is necessary.
If you've used your code to any extent, you shouldn't have a problem
with the examples. If you've been in academia, you certainly have used
students as a resource to solve problems.
Thanks, CC.
Scott L. Burson
Jul 14, 2012, 11:24:46 PM7/14/12
to
Luke Hope <ruku...@gmail.com> wrote:
> I've been hanging on to some code I developed about 5-6 years ago when I was
> in academia. I'm wondering if I should open source it.
I would love to see this too!
> I've been hanging on to some code I developed about 5-6 years ago when I was
> in academia. I'm wondering if I should open source it.
-- Scott
David Hodge
Jul 16, 2012, 8:09:05 PM7/16/12
to
Jay Sulzberger
Jul 18, 2012, 4:49:31 PM7/18/12
to
This gift would be used.
I recommend using a standard free license, either a GPL, or a BSD
license, so as to lower the legal/psychic barrier to
using/hacking.
Thank you!
oo--JS.
D Herring
Jul 18, 2012, 9:07:54 PM7/18/12
to
On 07/18/2012 04:49 PM, Jay Sulzberger wrote:
> I recommend using a standard free license, either a GPL, or a BSD
> license, so as to lower the legal/psychic barrier to
> using/hacking.
The MIT and Boost licenses are also good.
> I recommend using a standard free license, either a GPL, or a BSD
> license, so as to lower the legal/psychic barrier to
> using/hacking.
http://www.boost.org/users/license.html
- Daniel
Jay Sulzberger
Jul 19, 2012, 2:15:13 AM7/19/12
to
be well known and widely used.
Here is the Wikipedia article on license proliferation:
http://en.wikipedia.org/wiki/Licence_proliferation
[page was last modified on 13 July 2012 at 13:06]
oo--JS.
Aleksej Saushev
Jul 19, 2012, 6:04:36 AM7/19/12
to
Jay Sulzberger <ja...@panix.com> writes:
> In <ju7mla$im1$1...@dont-email.me> D Herring <dher...@at.tentpost.dot.com> writes:
>
>> On 07/18/2012 04:49 PM, Jay Sulzberger wrote:
>
>>> I recommend using a standard free license, either a GPL, or a BSD
>>> license, so as to lower the legal/psychic barrier to
>>> using/hacking.
>>
>> The MIT and Boost licenses are also good.
>>
>> http://www.boost.org/users/license.html
>
> In <ju7mla$im1$1...@dont-email.me> D Herring <dher...@at.tentpost.dot.com> writes:
>
>> On 07/18/2012 04:49 PM, Jay Sulzberger wrote:
>
>>> I recommend using a standard free license, either a GPL, or a BSD
>>> license, so as to lower the legal/psychic barrier to
>>> using/hacking.
>>
>> The MIT and Boost licenses are also good.
>>
>> http://www.boost.org/users/license.html
>
> The main thing is that the license be a free license, and that it
> be well known and widely used.
>
> Here is the Wikipedia article on license proliferation:
>
> http://en.wikipedia.org/wiki/Licence_proliferation
> [page was last modified on 13 July 2012 at 13:06]
Do you mean that X11 is not used widely enough? Or what?
> be well known and widely used.
>
> Here is the Wikipedia article on license proliferation:
>
> http://en.wikipedia.org/wiki/Licence_proliferation
> [page was last modified on 13 July 2012 at 13:06]
--
HE CE3OH...
Jay Sulzberger
Jul 19, 2012, 6:12:55 PM7/19/12
to
standards. I do not have a sharply defined list, but certainly
most of the various GNU GPLs, most of the various BSD style
licenses, and MIT/X, are all free licenses, well known, widely
used, and so I recommend using one of these. Perhaps there are
other free licenses which are well known and widely used.
One more consideration: compatibility of licenses.
ON TO THE LISP PROBABILITY COMPUTATIONS!
oo--JS.
Luke Hope
Jul 20, 2012, 9:57:52 PM7/20/12
to
Hi all,
Thanks for the responses. I'll work on tidying it up to release it. As it is 4.5 years old (last real commit was 2007-12-15), it is pre-quicklisp and before I started working as a full time lisp dev. So you can understand the style and documentation are both lacking compared to my standards today.
I want to get it in a 'near-enough' state before release. I couldn't find any other libraries similar, so I will probably lay claim to 'cl-bayesnet' as the project name.
My plan is to release it with a BSD licence.
-Luke
On Thursday, July 19, 2012 6:49:31 AM UTC+10, Jay Sulzberger wrote:
> In <20760e57-a531-4356...@googlegroups.com> Luke Hope <ruku...@gmail.com> writes:
>
> > Hi all,
> >
> > I've been hanging on to some code I developed about 5-6 years
> > ago when I was in academia. I'm wondering if I should open
> > source it.
> >
> > It is a native pure lisp Bayesian Network inference engine. It
> > has two types of compilation:
> >
> >1. 'Standard' Join Tree such as implemented by e.g. Netica circa 2008.
> >
> >2. Arithmetic Circuits, which was a new research direction at the time.
> >
> > The arithmetic circuit module is able to compile a Bayesian
> > Network to lisp, C or Java standalone source code. That is, you
> > don't need any libraries at all to perform probabilistic
> > inference.
> >
> > Just curious.
Thanks for the responses. I'll work on tidying it up to release it. As it is 4.5 years old (last real commit was 2007-12-15), it is pre-quicklisp and before I started working as a full time lisp dev. So you can understand the style and documentation are both lacking compared to my standards today.
I want to get it in a 'near-enough' state before release. I couldn't find any other libraries similar, so I will probably lay claim to 'cl-bayesnet' as the project name.
My plan is to release it with a BSD licence.
-Luke
On Thursday, July 19, 2012 6:49:31 AM UTC+10, Jay Sulzberger wrote:
> In <20760e57-a531-4356...@googlegroups.com> Luke Hope <ruku...@gmail.com> writes:
>
> > Hi all,
> >
> > I've been hanging on to some code I developed about 5-6 years
> > ago when I was in academia. I'm wondering if I should open
> > source it.
> >
> > It is a native pure lisp Bayesian Network inference engine. It
> > has two types of compilation:
> >
> >1. 'Standard' Join Tree such as implemented by e.g. Netica circa 2008.
> >
> >2. Arithmetic Circuits, which was a new research direction at the time.
> >
> > The arithmetic circuit module is able to compile a Bayesian
> > Network to lisp, C or Java standalone source code. That is, you
> > don't need any libraries at all to perform probabilistic
> > inference.
> >
> > Just curious.
Jay Sulzberger
Jul 21, 2012, 4:12:35 AM7/21/12
to
> Thanks for the responses. I'll work on tidying it up to release it. As it i=
> s 4.5 years old (last real commit was 2007-12-15), it is pre-quicklisp and =
> before I started working as a full time lisp dev. So you can understand the=
> ny other libraries similar, so I will probably lay claim to 'cl-bayesnet' a=
Thanks!
oo--JS.
> s 4.5 years old (last real commit was 2007-12-15), it is pre-quicklisp and =
> before I started working as a full time lisp dev. So you can understand the=
> style and documentation are both lacking compared to my standards today.
>
> I want to get it in a 'near-enough' state before release. I couldn't find a=
>
> ny other libraries similar, so I will probably lay claim to 'cl-bayesnet' a=
> s the project name.
>
> My plan is to release it with a BSD licence.
>
> -Luke
FORWARD BEARING JOIN TREES!
>
> My plan is to release it with a BSD licence.
>
> -Luke
Thanks!
oo--JS.
Sam Steingold
Jul 22, 2012, 12:29:51 PM7/22/12
to
> * Luke Hope <ehxh...@tznvy.pbz> [2012-07-12 19:55:55 -0700]:
note that a small Bayes library is already available as CLOCC/CLLIB/bayes.lisp
http://clocc.hg.sourceforge.net/hgweb/clocc/clocc/raw-file/d9547a32bff6/src/cllib/bayes.lisp
--
Sam Steingold (http://sds.podval.org/) on Ubuntu 12.04 (precise) X 11.0.11103000
http://www.childpsy.net/ http://think-israel.org http://openvotingconsortium.org
http://jihadwatch.org http://camera.org http://dhimmi.com http://truepeace.org
Is there another word for synonym?
>
> I've been hanging on to some code I developed about 5-6 years ago when I
> was in academia. I'm wondering if I should open source it.
sure.
> I've been hanging on to some code I developed about 5-6 years ago when I
> was in academia. I'm wondering if I should open source it.
note that a small Bayes library is already available as CLOCC/CLLIB/bayes.lisp
http://clocc.hg.sourceforge.net/hgweb/clocc/clocc/raw-file/d9547a32bff6/src/cllib/bayes.lisp
--
Sam Steingold (http://sds.podval.org/) on Ubuntu 12.04 (precise) X 11.0.11103000
http://www.childpsy.net/ http://think-israel.org http://openvotingconsortium.org
http://jihadwatch.org http://camera.org http://dhimmi.com http://truepeace.org
Is there another word for synonym?
Luke Hope
Jul 22, 2012, 6:15:58 PM7/22/12
to s...@gnu.org
Hi Sam,
Thanks for the heads up, but note that Naive Bayes (as implemented in that library) is not at all the same as a Bayesian Network. Naive Bayes makes heavy assumptions about variable dependence (hence its Naivety), to make the probability calculations very simple.
You *can* implement a Naive Bayes classifier/model using Bayesian Network modelling, but the limitations of the Naive Bayes model means the vice-versa does not apply.
Again, thanks for your diligence!
-Luke
On Monday, July 23, 2012 2:29:51 AM UTC+10, sds wrote:
> > * Luke Hope <ehxh...@tznvy.pbz> [2012-07-12 19:55:55 -0700]:
> >
> > I've been hanging on to some code I developed about 5-6 years ago when I
> > was in academia. I'm wondering if I should open source it.
Thanks for the heads up, but note that Naive Bayes (as implemented in that library) is not at all the same as a Bayesian Network. Naive Bayes makes heavy assumptions about variable dependence (hence its Naivety), to make the probability calculations very simple.
You *can* implement a Naive Bayes classifier/model using Bayesian Network modelling, but the limitations of the Naive Bayes model means the vice-versa does not apply.
Again, thanks for your diligence!
-Luke
On Monday, July 23, 2012 2:29:51 AM UTC+10, sds wrote:
> > * Luke Hope <ehxh...@tznvy.pbz> [2012-07-12 19:55:55 -0700]:
> >
> > I've been hanging on to some code I developed about 5-6 years ago when I
> > was in academia. I'm wondering if I should open source it.
Luke Hope
Apr 7, 2013, 10:49:27 PM4/7/13
to
Hi all,
I am slightly embarrassed that it is 9 months since I wrote the initial expression of interest for releasing this code. But life happens.
Anyway, I have done sufficient polishing to release CL-BAYESNET into the wild:
https://github.com/lhope/cl-bayesnet
I chose to use the LLGPL.
API Documentation: https://github.com/lhope/cl-bayesnet/wiki/API-Documentation
Example code: https://github.com/lhope/cl-bayesnet/blob/master/tests/test-alarm.lisp
Enjoy! I will work on getting this registered with quicklisp soon.
-Luke
I am slightly embarrassed that it is 9 months since I wrote the initial expression of interest for releasing this code. But life happens.
Anyway, I have done sufficient polishing to release CL-BAYESNET into the wild:
https://github.com/lhope/cl-bayesnet
I chose to use the LLGPL.
API Documentation: https://github.com/lhope/cl-bayesnet/wiki/API-Documentation
Example code: https://github.com/lhope/cl-bayesnet/blob/master/tests/test-alarm.lisp
Enjoy! I will work on getting this registered with quicklisp soon.
-Luke
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