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...

利用人工智能原理中BP神经网络算法，建立的彩票预测程序，当然不可能都预测中，但是要学习神经网络的人值得一看-BP neural network algorithm, the establishment of the lottery forecasting process, of course, not all forecasts, but neural networks to study the eye-catcher

这是我帮一个本科生做的毕业设计，实现的数据挖掘的k均值和k中心算法，其中包含了我做的两个二维的数据集，感觉要预先知道k的参数值，不是很方便-This is what I do to help an undergraduate graduation Design, Implementation of the Data Mining mean k and k center algorithm, which includes me to do two two-dimensional data sets, feeling to know beforehand the value of the parameter k is not easy

基于机器学习的自动逻辑推理机。本程序用归结反演策略实现了命题逻辑系统的自动推理。把要解决的问题作为一个要证明的命题，其目标公式被否定并化成子句形，然后添加到命题公式集中去,把消解反演系统应用于联合集，并推导出一个空子句(NIL)，产生一个矛盾。-based on the automatic machine learning logical reasoning machine. The procedures used attributed inversion strategy to achieve the propositional logic of automatic reasoning. Put the problem to be solved as a proposition to prove, with the goal being negated formula and shape into a phrase and then added to the Proposition formula to concentrate, digestion system for joint inversion sets and derived an empty phrase (NIL), resulting in a contradiction.

利用小波函数做神经网络的激活函数 这是一个简单的方法在使用BP网络的时候 可以直接调用小波函数 -Does the use of wavelet function neural network activation function is a simple method in the use of BP networks can directly call the wavelet function

这是一篇关于文本分类问题的综述，详细的介绍了文本分类的技术发展。-text category

数据挖掘中ID3分类算法的vc实现的源代码-Data Mining ID3 classification algorithm to achieve the vc source code

使用线性分类器进行分类，采用感知器算法中的“奖惩算法”，各提取3类中的前25个样本共75个作为学习样本。-The use of a linear classifier for classification, perceptron algorithm using the reward and punishment algorithm , the extraction of 3 categories of the top 25 a total of 75 samples as the learning samples.

遗传算法神经网络，遗传算法神经网络遗传算法神经网络-genetic algorithm neural networks, genetic algorithms neural networks, genetic algorithm, neural network

简单的遗传算法源代码，挺实用的，大家可以借鉴-Simple genetic algorithm source code, very useful, we can learn from

改进的遗传算法，有兴趣的可以下-Improved genetic algorithms, are interested in can be done next