写一段反向传播神经网络算法完整代码
时间: 2023-03-15 11:55:41 浏览: 75
反向传播神经网络算法的完整代码如下:def backpropagation(weights, inputs, targets):
# 计算输入到输出的激活值
outputs = forward_propagation(weights, inputs)
# 计算输出层的误差
output_errors = [outputs[i] - targets[i] for i in range(len(targets))]
# 计算隐藏层的误差
hidden_errors = [0.0] * len(weights[0])
for j in range(len(weights[0])):
for k in range(len(output_errors)):
hidden_errors[j] += output_errors[k] * weights[1][k][j]
# 更新权重
for i in range(len(weights[0])):
for j in range(len(weights[0][i])):
weights[0][i][j] -= inputs[j] * hidden_errors[i] * 0.1
for i in range(len(weights[1])):
for j in range(len(weights[1][i])):
weights[1][i][j] -= outputs[i] * output_errors[j] * 0.1
return weights