Support vector machines (5) libsvm

自己编的遗传算法同BP神经网络结合的代码！并且在神经网络模型上进行多目标寻优，结果有doc文档详细说明！实现BP-GA多目标优化应用实例！-Own genetic algorithm with BP neural network combined with the code! And in the neural network model for multi-objective optimization, the result document has a detailed description doc! Realize BP-GA multi-objective optimization application examples!

WEKA 3-5-5 Explorer 用户指南 原中文版-Explorer how to use weka 2-5-5

模式识别中关于感知器算法的程序,输入点进行聚类.-pattern recognition algorithm on the perception of the process, input cluster.

7。《进化算法》，云庆夏编着 冶金工业出版社 2000年第一版 全书共分5章，分别为绪论、遗传算法、遗传规划、进化策略、进化规划。-7. "Evolutionary algorithm," Yun Qing Xia compile Metallurgical Industry Publishing House in 2000 the first edition of the book is divided into five chapters, each of the introduction, Genetic algorithms, genetic programming, evolutionary strategy, evolutionary programming.

一个基本遗传算法求函数最大值的程序，在Vc中运行结果很好，有详细的代码注释，可以做为模板使用。 sag_sag.c-a basic function of genetic algorithms for maximum procedures, the Vc running good results, a detailed source notes, can be used as a template. Sag_sag.c

神经网络模式识别及其实现，第四章。 内含：ALOPEX和BACKPROP程序。-pattern recognition and neural network to achieve, the fourth chapter. Intron : ALOPEX BACKPROP and procedures.

一个很好的bp神经网络预测程序实例，有较好的预测精确性-Bp a good example of neural network forecasting process, a better prediction accuracy

这是一个parzen窗口分类算法，希望能给大家的学习有所帮助-This is a Parzen window classification algorithm, we hope that they will be helpful to the learning

//开发平台：Microsoft .NET Framework 2.0，Microsoft Visual C# 2005 Express //日期：2005.3.12 //作者：刘波 //粒子群优化算法(PSO)：本算法求目标函数的最小值-//development platforms : Microsoft.NET Framework 2.0, Microsoft Visual C# 2005 Express// Date : 2005.3.12// Author : Liu Bo// Particle Swarm Optimization (PSO) : The algorithm for the minimum objective function

本人编写的QR分解的神经网络算法，该算法用QR分解神经网络的隐含层矩阵，可以作为学术上的比较和分析。适合各种benchmark问题，本人还加了自动产生分类向量和自动适应各种函数的例子-I prepared the QR decomposition of neural network algorithm using QR decomposition neural network hidden layer matrix, can be used as an academic comparison and analysis. Suitable for a variety of benchmark problems, I also added automatically generated classification and automatic vector function to adapt to a variety of examples