RE: Neural Network Programming Overview Question
- From: "Pranav Lal" <pranav.lal@xxxxxxxxx>
- To: <programmingblind@xxxxxxxxxxxxx>
- Date: Fri, 17 Oct 2008 06:10:44 +0530
Rick,
What will you use for your base data? That is, will you start from something
like yahoo stock quotes? I dream of being able to write my own stock trading
agent some day though right now I will be content to write a good technical
analysis application. <chuckle
Needless to say, I am following this thread with much interest.
Pranav
-----Original Message-----
From: programmingblind-bounce@xxxxxxxxxxxxx
[mailto:programmingblind-bounce@xxxxxxxxxxxxx] On Behalf Of Ricks Place
Sent: Thursday, October 16, 2008 4:39 PM
To: programmingblind@xxxxxxxxxxxxx
Subject: Re: Neural Network Programming Overview Question
Thanks for the help Sina and Black:
This is just my closing blurb on what I found and my direction going
forward.
I reviewed all the articles and websites Sina sent me and many others. I
have decided to do my AI work in Vb.net, or if necessary C#.
My Reasoning: There are plenty of code examples and libraries for them, I am
very comfortable with the languages and IDE and, finally, the whole subject
of Neural Networks is going to take massive research and experimentation on
my part. This way I can eliminate the learning curve of LISP, perhaps more
than one dialect and testing various compilers or IDE products for
accessibility, execution speed and features. In addition the diferent
third-party products and libraries all seem to use diferent forms of
Back-Propigation, Genetic and Linear processing as well as other
algorithms. This is the same for VS so is a wash in my decision. So, I am
already set up to start programming a Neural Network from the ground up with
some very simple examples which will help me learn the subject matter
without first setting up and learning a LISP Environment.
I can concentrate on the proper use of the algorithms, Data acquisition,
Model Testing and various results from various forms of the basic NN types.
That is, Predictive, Category and others I forget off-hand.
So thanks for the help in making my decision on how to break into this field
and I'm off to look for some more sample projects, libraries to pick one to
begin with.
Rick USA
----- Original Message -----
From: "Sina Bahram" <sbahram@xxxxxxxxx>
To: <programmingblind@xxxxxxxxxxxxx>
Sent: Wednesday, October 15, 2008 6:39 PM
Subject: RE: Neural Network Programming Overview Question
>
> Forward them along if you don't mind.
>
> Take care,
> Sina
>
> -----Original Message-----
> From: programmingblind-bounce@xxxxxxxxxxxxx
> [mailto:programmingblind-bounce@xxxxxxxxxxxxx] On Behalf Of black ares
> Sent: Wednesday, October 15, 2008 6:15 PM
> To: programmingblind@xxxxxxxxxxxxx
> Subject: Re: Neural Network Programming Overview Question
>
> I think I have some where some Ai books and genetic algorithms.
> Please e-mail offlist and I will try to answer with some books.
>
>
> ----- Original Message -----
> From: "Sina Bahram" <sbahram@xxxxxxxxx>
> To: <programmingblind@xxxxxxxxxxxxx>
> Sent: Wednesday, October 15, 2008 11:01 PM
> Subject: RE: Neural Network Programming Overview Question
>
>
>> There are probably millions of lines of lisp you can pull from for
>> libraries
>> and things of that nature for neural networks of varying types and
>> flavors.
>> Please note that's equivalent, literally, to hundreds of millions of
>> lines
>> of code of C# or other lesser languages, *smile*.
>>
>> Here are some random, and not so random links below.
>>
>> An interesting guy who has done research related to what you're asking
>> about.
>> http://www.idsia.ch/~juergen/
>>
>> A common strategy, and one of the few that actually has a chance in my
>> opinion, is evolutionary techniques that evolve neural networks. To that
>> end, here you go.
>>
>> Neurocomputing : Neural network construction and training using
>> grammatical
>> evolution:
>>
>
http://www.sciencedirect.com/science?_ob=ArticleURL&_udi=B6V10-4S1C894-3&_us
>>
>
er=10&_rdoc=1&_fmt=&_orig=search&_sort=d&view=c&_version=1&_urlVersion=0&_us
>> erid=10&md5=9736cb76398111c4e1306f5d31ec18de
>>
>> Watch out if links wrap ... That one's a long one, for example.
>>
>> Using multi-agents to predict the stock market evolution based on
>> fundamentalist analysis and fuzzy-neural networks
>> http://portal.acm.org/citation.cfm?id=1366414
>>
>> Designing neural networks using genetic algorithms:
>>
>
http://citeseerx.ist.psu.edu/showciting;jsessionid=6F2C4C9E46A26B6323421B306
>> 2D5B2F2?cid=65706
>>
>> Here's a general collection that might be useful:
>> Keith Price Bibliography New Unsorted Entries, and Other Miscellaneous
>> Papers
>>
>> Comparison of artificial intelligence & machine learning algorithms as a
>> predictor of surgical outcomes in benign prostatic hperlasia cases (BPH):
>> http://cat.inist.fr/?aModele=afficheN&cpsidt=14046882
>>
>> An Analysis of Factors Directing the Admission Process of Artificial
>> Intelligence Technologies
>> http://dbpubs.stanford.edu:8090/pub/1995-16
>>
>> Note: I think that last one has the full text available.
>>
>> Stock Market Modeling Using Genetic Programming Ensembles
>> http://www.springerlink.com/content/w061315720425n76/
>>
>> Connectionism
>> http://www.linuxselfhelp.com/HOWTO/AI-Alife-HOWTO-3.html
>>
>> Now for some code related links:
>>
>> Common-Lisp.net
>> http://common-lisp.net/
>>
>> C liki wiki:
>> http://www.cliki.net/index
>>
>> The Common Lisp Open Code Collection (CLOCC)
>> http://clocc.sourceforge.net/
>>
>> The common lisp hyperspec, this is most likely the most important link
>> out
>> of the whole bunch:
>> http://www.lispworks.com/documentation/HyperSpec/index.html
>>
>> Tour de Lisp
>>
>
http://tourdelisp.blogspot.com/2008/01/common-lisp-libraries-victims-of-driv
>> e.html
>>
>> Read the comments on that site, too.
>>
>> Anyways, hope that helps.
>>
>> Take care,
>> Sina
>>
>> ________________________________
>>
>> From: programmingblind-bounce@xxxxxxxxxxxxx
>> [mailto:programmingblind-bounce@xxxxxxxxxxxxx] On Behalf Of Ricks Place
>> Sent: Wednesday, October 15, 2008 2:53 PM
>> To: programmingblind@xxxxxxxxxxxxx
>> Subject: Neural Network Programming Overview Question
>>
>>
>> Hi Guys:
>> See if this sounds right:
>> A neural network may be any of several types.(models) MLP
>> FeedForward, BiDirectional models and many other Dynamic
>> variations. Inputs can be Filtered, weighted and tuned using
>> Back-Propagation, Genetics, Fuzzy Logic and Chaos Methods which
>> seem to be the ones best suited to Stock Market and Asset
>> Allocation based on Technicals and fundementals. LISP is the
>> programming language of choice for most programmers in the AI
>> field but is not supported in Visual Studio. If I hand code I
>> would have to code all of the models of a given network if I
>> wanted to evaluate each model's effectivness in prediction of
>> optimum Asset Allocation or Market Timing. There may, or not, be
>> modules, dlls? out there for Back-Propagation, Genetics and Fuzzy
>> Logic I could use in a home grown LISP application. There might be
>> some LISP based development environments for developing Neural
>> Networks available with embedded heavy math functions already set
>> up to apply against inputs for a LISP application.
>> Otherwise I would have to design and code them.
>> Do I have a generalized overview of the situation?
>> I am trying to decide on developing in LISP using just a LISP
>> environment, a specialized environment, a plug in for developing
>> NNs in Visual Studio, a Stand Alone system like NeuroShell or
>> something else like just subscribing to a service for investing
>> using the NeuroShell models.
>> Thanks Guys - this is really big time and I think I am just out of
>> my league but want to see if I have the general ideas before
>> making any initial decision costing allot of time, money or both.
>> Rick USA
>>
>>
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