我正在尝试学习如何从头开始编写非常简单的神经网络。但是我看不到如何进行正确的培训。每当我运行 while 循环时，它就会陷入无限循环。这是我的代码：
#inputs and targets
x1=[1,0,1]
x2=[0,1,0]
x3=[0,0,1]
inputs=[x1,x2,x3]
targets=[1,0,0,1]
#parameters
np.random.seed(1)
w1 = np.random.random_sample(size = 3)
w1=w1.tolist()
alpha=0.1
itera=0
#activation function
def purelin(z):
return z
#network
def red(i,w1):
n=[]
for inp in i:
a=inp*w1[inputs.index(i)]
n.append(a)
n=sum(n) #sumar inputs*weights (caso sin bias)
a=purelin(n)
return a
#forward propagation
def forw(inputs):
outputs=[]
for i in inputs:
x=red(i,w1)
outputs.append(x)
return outputs
#error
def error(targets, outputs):
e=[]
zip_object = zip(targets, outputs)
for i, j in zip_object:
e.append(i-j)
return e
#backpropagation
def back(e):
w1_=[] …