针对分类问题的单隐层前馈神经网络模型
以下代码片内容为周志华著《机器学习》习题5.5的自编程序。
# 周志华《机器学习》习题5.5 import random import numpy as np import matplotlib.pyplot as plt DataSet = [[0.697,0.460,1,0], [0.774,0.376,1,0], [0.634,0.264,1,0], [0.608,0.318,1,0], [0.556,0.215,1,0], [0.403,0.237,1,0], [0.481,0.149,1,0], [0.437,0.211,1,0], [0.666,0.091,0,1], [0.243,0.267,0,1], [0.245,0.057,0,1], [0.343,0.099,0,1], [0.639,0.161,0,1], [0.657,0.198,0,1], [0.360,0.370,0,1], [0.593,0.042,0,1], [0.719,0.103,0,1]] AttrSet = ['Density','Sugar','Quality'] NumInCell = 2 NumMidCell = 8 NumOutCell = 2 Vih = [[random.random()*1 for m in range(NumInCell)] for n in range(NumMidCell)] Rh = [random.random()*1 for m in range(NumMidCell)] Whj = [[random.random()*1 for m in range(NumMidCell)] for n in range(NumOutCell)] Sj = [random.random()*1 for m in range(NumOutCell)] MaxTimes = 10000 Time = 0 Yeta = 1 Loss = [] while Time
