Backprop is used to compute the gradient here <https://github.com/apache/spark/blob/master/mllib/src/main/scala/org/apache/spark/ml/ann/Layer.scala#L579-L584>, which is then optimized by SGD or LBFGS here <https://github.com/apache/spark/blob/master/mllib/src/main/scala/org/apache/spark/ml/ann/Layer.scala#L878>
On Mon, Sep 7, 2015 at 11:24 AM, Nick Pentreath <nick.pentre...@gmail.com> wrote: > Haven't checked the actual code but that doc says "MLPC employes > backpropagation for learning the model. .."? > > > > — > Sent from Mailbox <https://www.dropbox.com/mailbox> > > > On Mon, Sep 7, 2015 at 8:18 PM, Ruslan Dautkhanov <dautkha...@gmail.com> > wrote: > >> http://people.apache.org/~pwendell/spark-releases/latest/ml-ann.html >> >> Implementation seems missing backpropagation? >> Was there is a good reason to omit BP? >> What are the drawbacks of a pure feedforward-only ANN? >> >> Thanks! >> >> >> -- >> Ruslan Dautkhanov >> > >