针对分类问题的单隐层前馈神经网络模型

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5.5import randomimport numpy as npimport matplotlib.pyplot as pltDataSet = [[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 = 2NumMidCell = 8NumOutCell = 2Vih = [[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 = 10000Time = 0Yeta = 1Loss = []while Time