通过人工神经网络实现异或问题的解决，用visual c++开发

用matlab设计的概率神经网络，内附演示程序-using Matlab design of probabilistic neural network, enclosing Demonstration Program

神经网络C程序的第10章-neural network C procedures for the Chapter 10

Fuzzy Rule Base Implementation

K-mean算法实现程序-K-mean algorithm program! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! !

是国外相关研究人员提供的发现频繁模式（包括频繁集、频繁子图等）的最新版本算法。-Foreign researchers with the relevant frequent pattern discovery (including frequent itemsets, frequent subgraph, etc.) the latest version of algorithm.

用人工神经网络实现异或的功能。用反向传播算法（BP）来实现神经网络，正确率可以达到80% -using artificial neural network XOR functions. With back-propagation algorithm (BP) to achieve neural network, can achieve an accuracy rate of 80%

kmeans算法的java描述，我自己编写的，可以运行的-java kmeans algorithm description, I am prepared, ready-to-run

weka 的决策树的实现,对数据挖掘感兴趣的可以下哦,很好的呀-if you like Dataming

Machine Learning Weka 数据变换，给Arff文件加载权值，变换为XRFF文件。-Machine Learning Weka data transformation to Arff file to load the right value, transform paper to XRFF.

The Matlab Toolbox for Pattern Recognition