I am following this example to learn a bit about the use of auto-encoders in fraud detection. Now that I reached the end of the article, two questions rose in mind:

  1. Can we train the network in an unsupervised way, freeze the layers weights, add a sigmoid layer as an output then finally use this model as a binary classifier?
  2. Are auto-encoders considered as the state-of-the-art method in fraud detection? What other alternatives can be used in this case?
  • $\begingroup$ Do layer-wise training like Hinton for Deep Belief Networks, and then train a classifier with the internal representation $\endgroup$ – Andrea Guidi Mar 17 '19 at 14:11

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