import operator import time def createData(dim = 200, cnoise = 0.2): ''' 生成数据集 ''' x, y = sklearn.datasets.make_moons(dim, noise = cnoise) plt.scatter(x[:,0], x[:,1], s = 40, c=y, cmap=plt.cm.Spectral) return x,y def initSuperParameter(x): ''' 初始化超参数 ...
importnumpyasnp # ... code from previous section here classOurNeuralNetwork: ''' A neural network with: - 2 inputs - a hidden layer with 2 neurons (h1, h2) - an output layer with 1 neuron (o1) Each neuron has the same weights and ...
code from previous section here class OurNeuralNetwork: ''' A neural network with: - 2 inputs - a hidden layer with 2 neurons (h1, h2) - an output layer with 1 neuron (o1) Each neuron has the same weights and bias: - w = [0, 1] - b = 0 ''' def __init__(self): ...
A neural network with: - 2 inputs - a hidden layer with 2neurons(h1, h2) - an output layer with 1 neuron (o1) *** DISCLAIMER *** The code below is intend to be simple and educational, NOToptimal. Real neural net code looks nothing like this. Do NOT use this code. Instead, rea...
# ... code from previous section here classOurNeuralNetwork: ''' A neural network with: - 2 inputs - a hidden layer with 2 neurons (h1, h2) - an output layer with 1 neuron (o1) Each neuron has the same weights and bias:
这第一个部分是BP神经网络的建立 参数选取参照论文:基于数据挖掘技术的股价指数分析与预测研究_胡林林 importmathimportrandomimporttushare as tsimportpandas as pd random.seed(0)defgetData(id,start,end): df=ts.get_hist_data(id,start,end) DATA=pd.DataFrame(columns=['rate1','rate2','rate3','pos...
importnumpyasnp# ... code from previous section hereclassOurNeuralNetwork:''' A neural network with: - 2 inputs - a hidden layer with 2 neurons (h1, h2) - an output layer with 1 neuron (o1) Each neuron has the same weights and bias: - w = [0, 1] - b = 0 '''def__init...
# ... code from previous section here classOurNeuralNetwork: ''' A neural network with: - 2 inputs - a hidden layer with 2 neurons (h1, h2) - an output layer with 1 neuron (o1) Each neuron has the same weights and bias:
# python notebook for Make Your Own Neural Network # code for a 3-layer neural network, and code for learning the MNIST dataset # (c) Tariq Rashid, 2016 # license is GPLv2 import numpy # scipy.special for the sigmoid function expit() ...
"""network.py ~~~ A module to implement the stochastic gradient descent learning algorithm for a feedforward neural network. Gradients are calculated using backpropagation. Note that I have focused on making the code simple, easily readable, and easily modifiable. It is not optimized, and omits...