Does anybody know of a Neural Network solution in Smalltalk? I'm
especially interested in the classification of objects by symbolic attribute vectors (learning by example). Andre |
Andre Schnoor wrote:
> Does anybody know of a Neural Network solution in Smalltalk? I'm > especially interested in the classification of objects by symbolic > attribute vectors (learning by example). > > Andre I have an implementation of Hopfield nets and BAM's (Bidirectional Associative Memory) but I suspect it's not what you're looking for. David Buck |
In reply to this post by Andre Schnoor
not sure if this helps but there was a book once published entitled
"Advance Smalltalk" by jonathan Plentzke if I recall the name correctly, code for building a Neural Net was provided. Not sure how robust that was etc. hth, -Charles On Thu, 16 Mar 2006 11:09:42 -0500, Andre Schnoor <[hidden email]> wrote: > Does anybody know of a Neural Network solution in Smalltalk? I'm > especially interested in the classification of objects by symbolic > attribute vectors (learning by example). > > Andre -- Charles A. Monteiro |
In reply to this post by Andre Schnoor
Once upon a time (90- 95) there was a big Neural net application built
on the ST80 v.4.1. The application was used for the real client(Airline revenue management system) with reasonable enough success so it was even nominated for the "Smithsonian Award" or something similar in 94. I don't have any more information, but if properly motivated, I can try to dig up some names. -Mark Andre Schnoor wrote: > Does anybody know of a Neural Network solution in Smalltalk? I'm > especially interested in the classification of objects by symbolic > attribute vectors (learning by example). > > Andre > > > |
In reply to this post by davidbuck
Hi david
could you publish your code on one the cincom store? I feel that it would be good to packages of interesting libraries available (may be porting weka one would be good). Stef On 16 mars 06, at 17:08, David Buck wrote: > Andre Schnoor wrote: > >> Does anybody know of a Neural Network solution in Smalltalk? I'm >> especially interested in the classification of objects by symbolic >> attribute vectors (learning by example). >> >> Andre > > I have an implementation of Hopfield nets and BAM's (Bidirectional > Associative Memory) but I suspect it's not what you're looking for. > > David Buck > > |
In reply to this post by davidbuck
>> Does anybody know of a Neural Network solution in Smalltalk? I'm >> especially interested in the classification of objects by symbolic >> attribute vectors (learning by example). > > I have an implementation of Hopfield nets and BAM's (Bidirectional > Associative Memory) but I suspect it's not what you're looking for. > Not really. I'm looking for a simple object classification, i.e. input a vector of attributes (somehow mapped to numeric values) and output 1 out of n classes, trainable by examples. Possibly a similar solution like optical character recognition. Andre |
Charles mentioned the Advanced Smalltalk book, which I've just had a
quick look through. It contains an example of back-propagation, (translated directly from a poorly written C program - (his words)). He also mentions a "very well-architected" program by Murali Krishnan of UIUC. Apparently the source code is in the archives and includes three types of networks: a back-propagation, aHopfield net, and a self-organizing feature map network. (with UI's for VW). It also allows for other types of networks because of it's generic approach. Maybe useful? Cheers, Stewart >-----Original Message----- >From: [hidden email] [mailto:[hidden email]] >Sent: 17 March 2006 9:56 >To: vwnc-list >Subject: Re: Neuronal Network Training > > >>> Does anybody know of a Neural Network solution in Smalltalk? I'm >>> especially interested in the classification of objects by symbolic >>> attribute vectors (learning by example). >> >> I have an implementation of Hopfield nets and BAM's (Bidirectional >> Associative Memory) but I suspect it's not what you're looking for. >> >Not really. I'm looking for a simple object classification, i.e. input >vector of attributes (somehow mapped to numeric values) and output 1 out >of n classes, trainable by examples. Possibly a similar solution like >optical character recognition. > >Andre > |
Hi,
what's about to connect to SNNS http://www-ra.informatik.uni-tuebingen.de/SNNS/ ? it supports a wide range of networks, connecting to Smalltalk should not that difficult, becaus it has an API, if I remember right (I've implemented nets some years ago for SNNS). Also it runs on many systems. If someone would take a start for it I would help :-) Regards Hans -----Original Message----- > Date: Thu, 23 Mar 2006 05:52:36 +0100 > Subject: RE: Neuronal Network Training > From: "Stewart MacLean" > To: , > Charles mentioned the Advanced Smalltalk book, which I've just had a > quick look through. > > It contains an example of back-propagation, (translated directly from > a poorly written C program - (his words)). > > He also mentions a "very well-architected" program by Murali Krishnan > of UIUC. Apparently the source code is in the archives and includes > three types of networks: a back-propagation, aHopfield net, and a > self-organizing feature map network. (with UI's for VW). It also > allows for other types of networks because of it's generic approach. > > Maybe useful? > > Cheers, > > Stewart > > > > > -----Original Message----- > > From: [hidden email] [mailto:[hidden email]] > > Sent: 17 March 2006 9:56 > > To: vwnc-list > > Subject: Re: Neuronal Network Training > > > > > > > > Does anybody know of a Neural Network solution in Smalltalk? I'm > > > > especially interested in the classification of objects by > > > > symbolic attribute vectors (learning by example). > > > > > > > > > > I have an implementation of Hopfield nets and BAM's (Bidirectional > > > Associative Memory) but I suspect it's not what you're looking > > > for. > > > > > > > > Not really. I'm looking for a simple object classification, i.e. > > input > a > > vector of attributes (somehow mapped to numeric values) and output 1 > > > out > > of n classes, trainable by examples. Possibly a similar solution > > like optical character recognition. > > > > Andre > > > > > > > > |
interesting, it apparently is mostly C right? so it DLLCC-ed. There is now
of course a Java version and they undoubtedly used JNI. The only issue though for some may be the license. -Charles On Thu, 23 Mar 2006 02:39:30 -0500, [hidden email] <[hidden email]> wrote: > Hi, > > what's about to connect to SNNS > > http://www-ra.informatik.uni-tuebingen.de/SNNS/ ? > > it supports a wide range of networks, connecting to Smalltalk should not > that difficult, becaus it has an API, if I remember right (I've > implemented nets some years ago for SNNS). Also it runs on many systems. > > If someone would take a start for it I would help :-) > > Regards > > Hans > > -----Original Message----- >> Date: Thu, 23 Mar 2006 05:52:36 +0100 >> Subject: RE: Neuronal Network Training >> From: "Stewart MacLean" >> To: , > >> Charles mentioned the Advanced Smalltalk book, which I've just had a >> quick look through. >> >> It contains an example of back-propagation, (translated directly from >> a poorly written C program - (his words)). >> >> He also mentions a "very well-architected" program by Murali Krishnan >> of UIUC. Apparently the source code is in the archives and includes >> three types of networks: a back-propagation, aHopfield net, and a >> self-organizing feature map network. (with UI's for VW). It also >> allows for other types of networks because of it's generic approach. >> >> Maybe useful? >> >> Cheers, >> >> Stewart >> >> >> >> > -----Original Message----- >> > From: [hidden email] [mailto:[hidden email]] >> > Sent: 17 March 2006 9:56 >> > To: vwnc-list >> > Subject: Re: Neuronal Network Training >> > >> > >> > > > Does anybody know of a Neural Network solution in Smalltalk? I'm >> > > > especially interested in the classification of objects by >> > > > symbolic attribute vectors (learning by example). >> > > > >> > > >> > > I have an implementation of Hopfield nets and BAM's (Bidirectional >> > > Associative Memory) but I suspect it's not what you're looking >> > > for. >> > > >> > > >> > Not really. I'm looking for a simple object classification, i.e. >> > input >> a >> > vector of attributes (somehow mapped to numeric values) and output 1 >> > >> out >> > of n classes, trainable by examples. Possibly a similar solution >> > like optical character recognition. >> > >> > Andre >> > >> > >> >> >> >> > > -- Charles A. Monteiro |
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