신경망 각 층의 구현(분류)

import numpy as np

import matplotlib.pyplot as plt

X = np.arange(-1.0, 1.0, 0.1)

Y = np.arange(-1.0, 1.0, 0.1)

w_im = np.array([[1.0,2.0],[2.0,3.0]])

w_mo = np.array([[-1.0,1.0],[1.0,-1.0]])

b_im = np.array([0.3,-0.3])

b_mo = np.array([0.4,0.1])

def middle_layer(x, w, b):

    u = np.dot(x, w) + b

    return 1/(1+np.exp(-u))

def output_layer(x, w, b):

    u = np.dot(x, w) + b

    return np.exp(u)/np.sum(np.exp(u))

x_1 = []

y_1 = []

x_2 = []

y_2 = []

for i in range(20):

    for j in range(20):

       

        inp = np.array([X[i],Y[j]])

        mid = middle_layer(inp, w_im, b_im)

        out = output_layer(mid, w_mo, b_mo)

       

        if out[0] > out[1]:

            x_1.append(X[i])

            y_1.append(Y[j])

        else:

            x_2.append(X[i])

            y_2.append(Y[j])

           

plt.scatter(x_1, y_1, marker="+")

plt.scatter(x_2, y_2, marker="o")

plt.show()