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INTELLIGENCE COMPUTATIONAL

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COMPUTATIONAL INTELLIGENCE

Implementation of a Deep MLP Classifier using Self-Organizing Maps for Feature Extraction

Adrian Horzyk

LABORATORY CLASSES

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Use SOM in your MLP Classifier

In the first layer of the previously developed MLP network add unsupervised trained SOM for

initial features extraction and develop the deep MLP Classifiers for the Iris data. Use all output

neurons of SOM as inputs to MLP network. Compare results with the previous solutions.

(3)

Use SOM in your MLP Classifier

First, create a SOM network and train it to get groups of training samples represented by its nodes.

Second, use all SOM outputs computed for each original input data to stimulate the MLP Network instead of using the original input data. You can also use both on the input of the MLP network.

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