数据挖掘中很不错的源码,一个share算法的java源程序,有极好的可读性...

神经网络模式识别及其实现，第三章。为大家提供参考。-pattern recognition and neural network to achieve, the third chapter. To provide a reference.

神经网络OOP类库，含有BP网络等的训练，很容易对其进行扩展，-neural network OOP libraries, containing BP network of training, it is easy to extend them

人工智能经典问题TSP问题的C语言实现，内含源程序和调试过程生成的文件-AI classic TSP"s C language, and includes source code debugging process produces files

模拟退火和遗传算法混和求解车辆路径问题的程序，没有解压密码。-simulated annealing and genetic algorithms hybrid vehicle routing problem solving process, not extracting passwords.

遗传算法的一个库，算法设置比较灵活，需要懂算法的人来下载-a genetic algorithm library, set up a more flexible algorithm, the algorithm needs to understand people to download

every function has its own help which can be obtained by typing "help name" where "name" is the function, e.g. "help fcm"-every function has its own help which can be obtained by typing "help name" where "name" is t he function, eg "help FCM"

此为疾病诊断专家系统，用这种结构建立的知识库可以很方便地实现上面所提到的各种功能。这种结 构的最独特之处就是依靠相同的关键（疾病名或其代码）来实现一种疾病与其症候之 间的相互联系。疾病名与症候分别用二叉树进行排序。排序后可由疾病名而查到与该 疾病名有关的所有详细情况，也可由一种症候而查到哪些疾病有这种症候，以及该症 候可能引起各种疾病的概率。-This is the disease diagnosis expert system, using this structure to establish the knowledge base can easily realize the above mentioned features. The structure of the most unique is that relying on the same key (the disease or its code) to achieve a disease and its symptoms between. Name and symptoms of disease were treated with binary tree sort. Sort by the disease after the name of the disease were found with all the details of which can also be a symptom of the diseases that have found such a symptom, as well as the symptoms may lead to the probability of various diseases.

clementine8.1白皮书经典的数据挖掘软件说明-clementine8.1 White Paper classical data mining software Note

eview 编写的时间序列预报程序 可以用于金融预报，等-eview the preparation of time-series forecasting procedures can be used for financial forecasting, etc.

模式识别一份很好的作业,包括线性分类器；最小风险贝叶斯分类器；监督学习法分层聚类分析；K－L变换提取有效特征,支持向量机-a very good operation, including linear classification; Minimum risk Bayesian classifier; Supervised learning method Hierarchical clustering analysis; K-L transform effective features, support vector machines