I have read articles about feature extraction using neural networks, my understanding is that neural networks naturally extract high-order features based on the weights on the edges of the neural networks. Is it possible to extract these features from a patternnet or other matlab neural network implementations, and then use these features for other classifiers?
In particular, I am working with about 450 training examples, 13 classes and about 280 features, and I expect some combination of features (F1-F2)*(F3-90)/(F4-10) etc, to be very predictive of my class labels, but all of the feature extraction methods I have found only work for images and not general classification problems.
Any advice is appreciated
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