Here comes the first patch! hope it is working!
can be run with mapreduce or locally:
java org.apache.mahout.classifier.rbm.training.RBMClassifierTrainingJob --input dirOrFile --output pathWhereModelShouldBeWritten --labelcount 10 --epochs 30 --monitor
Training consists of 3 steps: initialize biases, greedy pretraining, finetuning... however it is possible to train the model on few of them at a time (options: --nogreedy --nobiases --nofinetuning
input has to be sequencefile of <IntWritable, VectorWritable> where the Integer is the label
org.apache.mahout.classifier.rbm.test.TestRBMClassifierJob should be clearer
Preparation of mnist dataset in examples:
"size" is number of examples being processed into "chunknumber" minibatches (or chunks), labelpath and imagepath refer to the training-/testdata from the mnist dataset
I am doing my own tests on the mnist dataset right now and it is nearly done. It is taking some time because its size but manageable. I can upload the trained model if someone wants it for testing.