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@arthurcvm
Created August 30, 2018 00:07
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PMC problemática na atualização.
import numpy as np
def sigmoid(soma):
return 1 / (1+np.exp(-soma))
def sigmoidDerivada(sig):
return sig * (1 - sig)
entradas = np.array([[0,0],
[0,1],
[1,0],
[1,1]])
saidas = np.array([[0],[1],[1],[0]])
pesos0 = np.array([[-0.424, -0.740, -0.961],
[0.358, -0.577, -0.469]])
pesos1 = np.array([[-0.017], [-0.893], [0.148]])
epocas = 100
taxaAprendizagem = 0.3
momento = 1
for j in range(epocas):
camadaEntrada = entradas
somaSinapse0 = np.dot(camadaEntrada, pesos0)
camadaOculta = sigmoid(somaSinapse0)
somaSinapse1 = np.dot(camadaOculta, pesos1)
camadaSaida = sigmoid(somaSinapse1)
erroCamadaSaida = saidas - camadaSaida
mediaAbsoluta = np.mean(np.abs(erroCamadaSaida))
derivadaSaida = sigmoidDerivada(camadaSaida)
deltaSaida = erroCamadaSaida * derivadaSaida
pesos1Transposta = pesos1.T
deltaSaidaXPeso = deltaSaida.dot(pesos1Transposta)
deltaCamadaOculta = deltaSaidaXPeso * sigmoidDerivada(camadaOculta)
camadaOcultaTransposta = camadaOculta.T
pesosNovo1 = camadaOcultaTransposta.dot(deltaSaida)
pesos1 = (pesos1 * momento) + (pesosNovo1 * taxaAprendizagem)
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