# Autoencoder anamoly detection

I recently learnt about the anamoly detection using autoencoders(specifically denoisinng autoencoders).To train the autoencoders do we need a data having some pattern? or is there some way to train in abnormal data ?Also how we decide that the data is suitable for training autoencoder model.

• Alternatively you could use something like Isolation Forest which allows you to include anomalous data in training. Check out sklearn's implementation and the contamination parameter. – Simon Larsson Feb 13 '20 at 11:00
• I think the variational autencoder is superior to the denoising autoencoder, specifically in the ability to generate new data. – Victor Ng Mar 14 '20 at 13:56