def __process(nrOfIterations, learningRate, hiddenNeuronsNumber, aConst):
dataset = ProblemData("resources/data.data")
trainX, trainY, testX, testY = dataset.splitData()
neuralNetwork = ANN(deepcopy(trainX), deepcopy(trainY), learningRate,
hiddenNeuronsNumber, aConst)
iterations = []
for i in range(nrOfIterations):
neuralNetwork.feedForward()
neuralNetwork.backProp()
iterations.append(i)
for i in range(len(testX)):
predictedOut = neuralNetwork.getOutput(testX[i])
print("Predicted output: {0}\nReal value: {1}".format(
predictedOut, testY[i]))
matplotlib.pyplot.plot(iterations,
neuralNetwork.getLoss(),
label='loss value vs iteration')
matplotlib.pyplot.xlabel('Iterations')
matplotlib.pyplot.ylabel('Loss function')
matplotlib.pyplot.legend()
matplotlib.pyplot.show()
