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Simple neural network classifier on the MNIST digit set

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digitNN

Simple neural network classifier on the MNIST digit set.

The neural network is a backpropagating softmax activated multimatrix with double variable sized hidden nodes layer that achieves 96% accuracy on default settings.

Comes with automatic training featuring epochs, mini-batches, automatic alpha adjustment and cutoff, validation error visualisation and hyperparamater configuration for many aspects of the training process.

Version 1.5

  • New dataset of around 300.000 handwritten letters
  • Parameter tweaking and cleanup
  • Epoch progress bar
  • Converter for .csv to .idx.gz files
  • 97% accuracy on the handwritten letters set

Version 1.1

  • Cross-entropy loss and softmax activation
  • Epoch based learning, automatic training data shuffling, deterministic batching
  • Automatic alpha decay
  • Validation error visualiser, see which samples the network got wrong
  • Average 96% accuracy after three minutes of training

Version: 1.0

  • Randomized mini-batch learning classifier by sigmoid activation
  • Sampler for user image prediction

Resources

Download the MNIST set yourself here since I have no explicit right to redistribute it.