[GitHub] spark issue #13621: [SPARK-10408] [ML] Implement stacked autoencoder

[JeremyNixon <gi...@git.apache.org>]

Github user JeremyNixon commented on the issue:

    https://github.com/apache/spark/pull/13621
  
    I ran the Keras experiment with code up at [[GitHub link] ](https://github.com/JeremyNixon/autoencoder) if anyone wants to build on this or replicate it.
    
    Running Seth’s example on the training data set, I was able to get the results below. 
    
    ![screen shot 2017-05-11 at 10 08 37 pm](https://cloud.githubusercontent.com/assets/4738024/25979615/9567a8bc-3697-11e7-81ed-be3fd073f4c5.png)
    
    I agree that we should add modern activation functions. More importantly, we should add improved optimizers and a modular API to make this valuable to real users. 
    
    I’m going to do a code review here and at scalable-deeplearning in the next few days regardless of the decision we make around this. I think that these improvements (activation functions, optimizers) should be a part of a flexible modular library if we want to give users a modern experience. 
    



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