Question

我使用Python 2.7的neurolab包建立了一个神经网络，如下所示（松散地基于https://pythonhosted.org/neurolab/ex_newff.html处的样本）。通常，当训练发生时（带有net.train()的行），信息将被打印到控制台，例如“达到最大列车时期数”。训练此网络通常需要＆gt; 15秒但是，看似随机且没有稍微改变代码，训练失败：没有输出消息打印到控制台并且分类不正确。

import neurolab as nl
import numpy as np
import matplotlib.pyplot as plt
from mpl_toolkits.mplot3d import Axes3D

def f(v):
    if np.linalg.norm(v) < 0.35: return 1
    elif np.linalg.norm(v) < 0.75: return 0
    else: return -1

# Create training set
print 'sampling'
x = (np.random.rand(500, 3)*2)-1
y = np.asarray([f(i) for i in x])

size = len(x)

inp = x.reshape(size,3)
tar = y.reshape(size,1)

# Create network 
print 'creating net'
net = nl.net.newff([[-1.5, 1.5]]*3, [10, 1])

# Train network
print 'training net'
net.init()
net.train(inp, tar, epochs=500, show=100, goal=0.02)

# Simulate network
print 'simulating net'
out = net.sim(inp)
out = np.asarray([int(round(i)) for i in out])

# Plot network results
print 'plotting'
fig = plt.figure()
ax = fig.add_subplot(111, projection='3d')

for i in xrange(len(out)):
    cls = 'g'
    if out[i] == 1: cls = 'b'
    elif out[i] == -1: cls = 'r'    
    ax.scatter(x[i][0], x[i][1], x[i][2], c=cls)
    #plt.scatter(x[i][0], x[i][1], c=cls)

plt.show()

为什么会发生这种情况，我该如何解决？

Neurolab随机无法训练

0 个答案: