Where can I find examples of applications for trained ART and SOM networks?

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SUMMARY

This discussion centers on the practical applications of trained Adaptive Resonance Theory (ART) and Self-Organizing Map (SOM) networks. Users express a common challenge: while training these neural networks is well-documented, guidance on utilizing them post-training is scarce. The conversation highlights that trained networks can be employed for clustering and classification tasks, enabling the identification of patterns within data. Participants seek resources, such as books, to deepen their understanding of practical applications for ART and SOM networks.

PREREQUISITES
  • Understanding of Adaptive Resonance Theory (ART) networks
  • Familiarity with Self-Organizing Maps (SOM)
  • Knowledge of supervised and unsupervised learning techniques
  • Basic proficiency in neural network training algorithms
NEXT STEPS
  • Research practical applications of ART networks in clustering and classification
  • Explore case studies on Self-Organizing Maps (SOM) for pattern recognition
  • Learn about the implementation of neural networks in real-world scenarios
  • Find recommended literature on ART and SOM applications
USEFUL FOR

Data scientists, machine learning practitioners, and students seeking to apply trained ART and SOM networks in practical scenarios will benefit from this discussion.

eoghan
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Hi!
I attended a class in neural networks and I learned something about ART and SOM.
I learned how to implement the learning algorithm, but then? I wasn't told how to use the trained net! I looked in Google and I didn't find much, everybody talks on how to train a neural net, but nobody says how to use it after the learning process.
Do you know a place where I can find examples of (simple) applications of trained ART and SOM?
 
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Er, it should be trained on its application, shouldn't it?
 
Yes, I was given a set of data and I was told how to train the net for those data. Now that I have a trained net for those data, what am I supposed to do? I mean, what can I do with that net?
 
eoghan said:
Yes, I was given a set of data and I was told how to train the net for those data. Now that I have a trained net for those data, what am I supposed to do? I mean, what can I do with that net?

What kind of data are you working with?

Depending on the data and the application, the idea will be to create a neural network that is able to to create some kind of internal representation of a system that should converge to the represent the actual output itself.

If you are trying to create for example a clustering or classification model, then what happens is that the initial data will 'train' the network to create a model for taking an input and classifying either in an unsupervised form (clustering) or in a supervised form (classification) so that with that model, you can feed in some input and the network will classify it according to how it was trained with the training data.

The classification of data (unsupervised or supervised) helps not only for learning but for the identification of patterns. By creating the right classifications (supervised or unsupervised) you are finding patterns and you can use this for learning either in the network, or in another application (like taking the results of the network and using it in another application).

If the neural network is an optimal representation of the model that you are analyzing, then what this network will represent is the minimal representation of the model in it's most compressed form. Most likely the model will not be an errorless 1-1 representation of the model (there will be likely be errors of some sort), but again the point is that the network itself is a good approximation.

How you actually make use of this depends on exactly what you had in mind when you trained the data and created the network and what the actual data is in context.
 
Uhm... I think I have a deep lack of knowledge of som and art... do you know any good book with applications where I can study them?
 

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