class XorNetwork:
def __init__(self, nTrain=1000, nInputs=2, nNeurCapas=(2, 3, 1)):
self.Network = NeuralNetwork(nInputs, nNeurCapas)
self.Inputs = []
self.Outputs = []
I1 = [0, 0]
I2 = [0, 1]
I3 = [1, 0]
I4 = [1, 1]
for i in range(nTrain):
self.Inputs.append(I1)
self.Inputs.append(I2)
self.Inputs.append(I3)
self.Inputs.append(I4)
self.Outputs.append([xor(I1[0], I1[1])])
self.Outputs.append([xor(I2[0], I2[1])])
self.Outputs.append([xor(I3[0], I3[1])])
self.Outputs.append([xor(I4[0], I4[1])])
self.Network.realTraining(self.Inputs, self.Outputs)
self.Network.feed([0, 0])
print(self.Network.getOutput())
class dataSet:
def __init__(self, nEpochs=500, nInputs=8, nNeurCapas=[8, 19]):
self.red = NeuralNetwork(nInputs, nNeurCapas)
self.lineList = trainReader()
self.outputList = []
shuffle(self.lineList)
self.outlist(self.lineList, self.outputList)
# self.datatrain(nEpochs)
print("Funciono Entrenamiento: CheckPoint 1")
self.dataList = dataReader()
self.dataOut = []
self.outlist(self.dataList, self.dataOut)
self.curveTraining()
def outlist(self, lineList, outList):
for i in lineList:
zerolist = [0] * 19
zerolist[i.pop(0)] = 1
outList.append(zerolist)
def datatrain(self, nEpoch):
for j in range(nEpoch):
#start = time.time()
self.red.realTraining(self.lineList, self.outputList)
#end = time.time()
#print(end - start)
def curveTraining(self):
totallineas = len(self.dataList)
contpres = 0.0
error = 0
xaprendizaje = []
yaprendizaje = []
xerror = []
yerror = []
for k in range(7):
for l in range(len(self.dataList)):
self.red.feed(self.dataList[l])
for m in range(len(self.red.output)):
absdif = abs(self.dataOut[l][m] - self.red.output[m])
if absdif < 0.5:
contpres += 1
error += absdif**2
contpres /= 19
contpres /= totallineas
xaprendizaje.append(k)
yaprendizaje.append(contpres)
contpres = 0
xerror.append(k)
yerror.append(error)
error = 0
self.datatrain(k * 100 + 100)
plt.figure(1)
plt.subplot(211)
plt.xlabel("Numero de Epochs")
plt.ylabel("Cura de Aprendizaje")
plt.plot(xaprendizaje, yaprendizaje, 'b-')
plt.subplot(212)
plt.xlabel("Numero de Epochs")
plt.ylabel("Error")
plt.plot(xerror, yerror, 'r-')
plt.show()
