模式识别分类程序，贝叶斯，神经网络分类训练程序，很不错啊...

基于遗传算法的基元识别与提取，C++源代码-Based on genetic algorithm identification and extraction of primitives, C++ Source code

Bayes分类器应用于IRIS数据集的例子-An example of Bayes Classifier applied on IRIS Data Set

svm_nu 分类源码 用于svm的分类编程同svm_c 相近-svm classification svm_nu source for the classification of programming with similar svm_c

本多功能自控系统软实验平台包括经典控制理论、现代控制理论、系统辨识、最优控制、智能控制等的软实验内容，其功能接近和部分超过了Matlab的自动控制工具箱，其人性化的中文界面，让使用者能轻松完成各种控制系统实验，是学习控制理论、设计控制系统的有力工具。-the multifunction control system experimental platform including soft classical control theory, the modern control theory, system identification, optimal control, intelligent control of the soft experiments, its function and some close over the Matlab toolbox control, the human interface to help users easily End into a variety of experimental control system, control theory is the study and design of the control system powerful tool.

weka机器学习系统（本站可下载）的拓展，简化了从关系数据库中提取数据-weka machine learning system (download site), the development of a simplified relational database from which to extract data

SVDD的工具箱，可以很好的处理一类分类问题，详见Support Vector Data Description一文-SVDD tools，can be used to process one class classification problem,for more details ,we refer to "Support Vector Data Description"

本程序是人工编写的bp神经网络，针对识别样本btw三类进行训练和识别。-This procedure is prepared bp artificial neural networks, btw samples for identification of three types of training and identification.

美国麻省理工大学教授人工智能的课件以及课后的习题相关-American University professor of artificial intelligence at MIT courseware and the exercises related to the after-school

贝叶斯算法是基于贝叶斯定理 P(H|X) = P(X|H)P(H) / P(X).。对于多属性的数据集，计算 P(X|Ci) 的开销非常大，为减低计算复杂度，我们做条件独立的假设，即给定元组的类标号，假定属性值有条件地相互独立，即在属性间不存在依赖关系。此程序仅为算法的一个实现，根据训练数据训练分类器-Bayesian algorithm is based on the Bayes theorem P (H | X) = P (X | H) P (H)/P (X).. For multi-attribute data sets, computing P (X | Ci) of the overhead is very large, in order to reduce the computational complexity, we do conditional independence assumption that a given tuple class label, it is assumed that property values conditionally independent of each other, that does not exist in the inter-attribute dependencies. This procedure is only an implementation of algorithm, according to training data classifier training

改进的BP算法程序,希望对大家有所帮助.如果需要，请-The BP algorithm to improve the process, everyone would like to help. If necessary, please take a look at.