Simple implementations of some machine-learning algorithms

In neurons pacakage we have:

Perceptron

Updates weights after processing each line. Calculated error based on quantizer function result.

Adaline

Adaptive linear neuron

Processes whole data set, and after that updateds weights. Uses activations function to find current error between expected result and current one.

Testing

to run tests:

go test ./..

Tests are based on Iris flower data set