_convertToOneOfMany in PyBrain

Question

I follow the PyBrain tutorial Classification with Feed-Forward Neural Networks and want to build my own classifier.

I do not understand how _convertToOneOfMany modifies outputs.

Why would initial operation alldata.addSample(input, [klass]) create more than one output neuron per class?

Answer 1

nevermind, here is doc explaining this stuff http://pybrain.org/docs/tutorial/datasets.html

Answer 2

Target number is [0,1,2], this function translate them to (001,010,100). This is because many algorithms work better if classes are encoded into one output unit per class

Answer 3

The relevant part in the docs is the page Using Datasets: classification – Datasets for Supervised Classification Training:

When doing classification, many algorithms work better if classes are encoded into one output unit per class, that takes on a certain value if the class is present. As an advanced feature, ClassificationDataSet does this conversion automatically:

However, this is not an satisfying answer as I don't understand either why there should be more than one output neuron per class in the first hand.

Update: I recommend using keras