Found a dropout commit from avulanov: https://github.com/avulanov/spark/commit/3f25e26d10ef8617e46e35953fe0ad1a178be69d
It probably hasn't made its way to MLLib (yet?). -- Ruslan Dautkhanov On Mon, Sep 7, 2015 at 8:34 PM, Feynman Liang <fli...@databricks.com> wrote: > Unfortunately, not yet... Deep learning support (autoencoders, RBMs) is on > the roadmap for 1.6 <https://issues.apache.org/jira/browse/SPARK-10324> > though, and there is a spark package > <http://spark-packages.org/package/rakeshchalasani/MLlib-dropout> for > dropout regularized logistic regression. > > > On Mon, Sep 7, 2015 at 3:15 PM, Ruslan Dautkhanov <dautkha...@gmail.com> > wrote: > >> Thanks! >> >> It does not look Spark ANN yet supports dropout/dropconnect or any other >> techniques that help avoiding overfitting? >> http://www.cs.toronto.edu/~rsalakhu/papers/srivastava14a.pdf >> https://cs.nyu.edu/~wanli/dropc/dropc.pdf >> >> ps. There is a small copy-paste typo in >> >> https://github.com/apache/spark/blob/master/mllib/src/main/scala/org/apache/spark/ml/ann/BreezeUtil.scala#L43 >> should read B&C :) >> >> >> >> -- >> Ruslan Dautkhanov >> >> On Mon, Sep 7, 2015 at 12:47 PM, Feynman Liang <fli...@databricks.com> >> wrote: >> >>> 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 >>>>> >>>> >>>> >>> >> >