Since the training methods for neural network largely requires a lot of iterations, it is not perfect suitable to implement it in MapReduce style.
Currently, the NeuralNetwork is implemented as an online learning model and the training is conducted via stochastic gradient descent. Moreover, currently version of NeuralNetwork is mainly used for supervised learning, so there is no RBM or Autoencoder. Regards, Yexi 2014-02-25 10:34 GMT-05:00 Maciej Mazur (JIRA) <[email protected]>: > Maciej Mazur created MAHOUT-1426: > ------------------------------------ > > Summary: GSOC 2013 Neural network algorithms > Key: MAHOUT-1426 > URL: https://issues.apache.org/jira/browse/MAHOUT-1426 > Project: Mahout > Issue Type: Improvement > Components: Classification > Reporter: Maciej Mazur > > > I would like to ask about possibilites of implementing neural network > algorithms in mahout during GSOC. > > There is a classifier.mlp package with neural network. > I can't see neighter RBM nor Autoencoder in these classes. > There is only one word about Autoencoders in NeuralNetwork class. > As far as I know Mahout doesn't support convolutional networks. > > Is it a good idea to implement one of these algorithms? > Is it a reasonable amount of work? > > > > -- > This message was sent by Atlassian JIRA > (v6.1.5#6160) > -- ------ Yexi Jiang, ECS 251, [email protected] School of Computer and Information Science, Florida International University Homepage: http://users.cis.fiu.edu/~yjian004/
