Hi Alexander, Thanks for the info. I modified the code and used sigmoid at latest layer. It worked correctly with 2-3 layer.
Thanks... On Tue, Feb 16, 2016 at 8:51 PM, Ulanov, Alexander <[email protected] > wrote: > Hi Hayri, > > > > The MLP classifier is multi-class (one class per instance) but not > multi-label (multiple classes per instance). The top layer of the network > is softmax > http://spark.apache.org/docs/latest/ml-classification-regression.html#multilayer-perceptron-classifier > that requires the outputs sum to 1. Public interface accepts vector-label > pairs. > > > > Best regards, Alexander > > > > *From:* Hayri Volkan Agun [mailto:[email protected]] > *Sent:* Monday, February 08, 2016 11:02 AM > *To:* user @spark > *Subject:* Spark LBFGS Error with ANN > > > > I am using Multilayer Percertron Classifier. In each training instance > there are multiple 1.0 in the ouput vector of the Multilayer Perceptron > Classifier. This is necessary. With small number of training data I am > getting the following error > > > > *ERROR LBFGS: Failure again! Giving up and returning. Maybe the objective > is just poorly behaved? * > > > > > > What is the problem? My objective output is a vector for instance : > > > > [1.0 0.0 0.0 1.0] is my label with 4 double values. My network topology is > 100,20,4. > > > > Thanks in advance > > Hayri Volkan Agun > > PhD. Student - Anadolu University > -- Hayri Volkan Agun PhD. Student - Anadolu University
