基于svm的机器学习文本分类方法，具有很好的借鉴意义

开发环境：Visual C++ .net2003 功能介绍：神经网络算法实验；分Console版本和MFC版本；主要用来求解TSP问题。-Development Environment: Visual C++. Net2003 function introduction: neural network algorithm experiments sub-Console version and MFC version mainly used to solve the TSP problem.

基于有限状态机的汉语数字语音端点检测.rar.rar格式为ｖｉｐ-based on the finite state machine language digital voice endpoint detection. Rar.rar format vip

该文档是清华大学的模式识别教程，该版本是网页版本，浏览非常方便，内容也非常详细，非常适合初学者，个人举得特别是支持向量机那一章描述很棒！-this document is from Tsinghua University,this is the html version,it is convenient to read, it is very suitable for the elementary readers,in my own opinion,the charter of svm is very detail and easily understandable.

bp神经网络技术用于步态识别的vc源程序

一个bp实现回归的nn程序，可以从中学习神经网络在回归中的应用-Bp realize a return nn procedures, neural networks can learn from the reunification of the application

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

一个高人的VC实现NN的程序。很不错。先运行Matrixbase.dsw,again arithmetic.dsw, next nnbp.dsw,final neuralNetWork.dsw.-an expert in VC NN procedures. Very good. First running Matrixbase.dsw, again arithmetic.dsw. next nnbp.dsw, final neuralNetWork.dsw.

最新的支持向量机工具箱，有了它会很方便 1. Find time to write a proper list of things to do! 2. Documentation. 3. Support Vector Regression. 4. Automated model selection. REFERENCES ========== [1] V.N. Vapnik, "The Nature of Statistical Learning Theory", Springer-Verlag, New York, ISBN 0-387-94559-8, 1995. [2] J. C. Platt, "Fast training of support vector machines using sequential minimal optimization", in Advances in Kernel Methods - Support Vector Learning, (Eds) B. Scholkopf, C. Burges, and A. J. Smola, MIT Press, Cambridge, Massachusetts, chapter 12, pp 185-208, 1999. [3] T. Joachims, "Estimating the Generalization Performance of a SVM Efficiently", LS-8 Report 25, Universitat Dortmund, Fachbereich Informatik, 1999. -The newest work tools of svm,it will be very convenient to have it.

简单的遗传算法的例子,对于遗传算法的初学者来说非常有用.-Simple genetic algorithm examples.it very helpful for the beginners of genetic algorithm

神经网络介绍的源码-neural network introduced by the source