I am searching for a good method to generate automated features from my dataset, which I can use to put in a classifier. My dataset contains signals (for example acceleration), so it is numeric.
I already tried autoencoder and sparsefilter, but they seem only to work properly if there are features available already.
My aim is to generate features from the dataset. Is there another algorithm I can try? Maybe a better neural network (with more hidden layers)? And if I can use a better neural network, how can I get the features out of it?
Every suggestion is very much appreciated!