Neural Network Example using MNIST Data Set
Scala
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README.md

Neural Network Example using MNIST Data Set

An example of neural networks implemented in Scala (with the jblas linear algebra library) for recognizing hand-written digits.

Building & Running the Example

Requires java and sbt.

Building and running:

$ sbt run

This will run the example in src/main/scala/example/FeedForwardExample.scala

Configuration Examples

2 layer network:

val network = NeuralNetwork(
  Layer(trainSet.numInputs, 50, HyperbolicTangent):+Layer(trainSet.numOutputs, SoftMax),
  objective = CrossEntropyError)

3 layer network:

val network = NeuralNetwork(
  Layer(trainSet.numInputs, 300, Logistic):+Layer(200, Logistic):+Layer(trainSet.numOutputs, SoftMax),
  objective = CrossEntropyError,
  weightDecay = 0.001)

Training

val trainer = Trainer(
  numIterations = 3000,
  miniBatchSize = 100,
  numParallel = 0, //Try using more of those cores!
  learningRate = ConstantRate(0.3), //Others to try: AnnealingRate(0.35, iterations = 5000)
  momentumMultiplier = 0.9, 
  gradientChecker = None, //To check gradients try: Some(GradientChecker(numChecks = 10, accuracy = 8))
  evalIterations = 1000)

trainer.train(network, trainSet)

Saving / Loading

NeuralNetwork.save(network,"my-network.obj")
val network = NeuralNetwork.load("my-network.obj")