本程序用C语言实现了集成神经网络解决广义异或问题。用神经网络集成方法做成表决网,可克服初始权值的影响,对神经网络分类器来说:假设有N个独立的子网,采用绝对多数投票法,再假设每个子网以1-p的概率给出正确结果,且网络之间的错误不相关,则表决系统发生错误的概率为 Perr = ( ) pk(1-p)N-k 当p<1/2时 Perr 随N增大而单调递减. 在工程化设计中,先设计并训练数目较多的子网,然后从中选取少量最佳子网形成表决系统,可以达到任意高的泛化能力。 -this pro

A very simple example of Neural Networks using back propagation This program is a simple example of Neural Networks using back propagation. My code has all basic functionalities like learning rate, load net, save net, etc. You can have as many layer

In pattern recognition, the k-nearest neighbor algorithm (k-NN) is a method for classifying objects based on closest training examples in the feature space. k-NN is a type of instance-based learning, or lazy learning where the function is only approx

// Author: Mohammed Ali Akbani // E-mail: duke@samwonline.com // Level : beginner // Please do not repost it in you name, and vote for me.

ID3算法流程如下： 1.如果节点的所有类标号相同，停止分裂； 2.如果没有feature可供分裂，根据多数表决确定该节点的类标号，并停止分裂； 3.选择最佳分裂的feature，根据选择feature的值逐一进行分裂；递归地构造决策树。-ID3 algorithm process is as follows: 1. If the node is the same for all class label, stop dividing 2. If there is no featur