代码.txt
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喜欢一个人丶
2024-08-22
count
warray
初始化
ann
np.array
maxtry
参数
learn
1,
0,
17.3 KB
#!/usr/bin/env python# -*- coding: utf-8 -*-# code:myhaspl@myhaspl.com# 8-10.pyimport numpy as npimport randomimport copyisdebug = False# x和d样本初始化train_x = [[4, 11], [7, 340], [10, 95], [3, 29], [7, 43], [5, 128]]d = [[1, 0], [0, 1], [1, 0], [0, 1], [1, 0], [0, 1]]warray_txn = len(train_x[0])warray_n = warray_txn * 4# 基本参数初始化oldmse = 10 ** 100fh = 1maxtrycount = 500mycount = 0.0if maxtrycount >= 20: r = maxtrycount / 5else: r = maxtrycount / 2# sigmoid函数ann_sigfun = Noneann_delta_sigfun = None# 总层数初始化，比非线性导数多一层线性层alllevel_count = warray_txn * 4# 非线性层数初始化hidelevel_count = alllevel_count - 1# 学习率参数learn_r0 = 0.002learn_r = learn_r0# 动量参数train_a0 = learn_r0 * 1.2train_a = train_a0expect_e = 0.05# 对输入数据进行预处理ann_max = []for m_ani in range(0, warray_txn): temp_x = np.array(train_x) ann_max.append(np.max(temp_x[:, m_ani]))ann_max = np.array(ann_max)def getnowsx(mysx, in_w): '''生成本次的扩维输入数据 ''' global warray_n mysx = np.array(mysx) x_end = [] for i in range(0, warray
count/warray_txn/初始化/ann_max/np.array/maxtry/参数/learn_r0/1,/0,/
count/warray_txn/初始化/ann_max/np.array/maxtry/参数/learn_r0/1,/0,/
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