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...

本程序是用c语言编写的基于决策树分类方法的数据挖掘算法，它对测试集进行分类，挖掘出潜在的规则-this procedure is used to prepare the language c decision tree classification based on the data mining algorithm, which tests set for classification, tapping the potential rules

运用遗传算法进行聚类分析，对基金的风格进行分类-The use of cluster analysis of genetic algorithm to classify the style of fund

基于java实现的遗传算法 神经网络 实数编码 交叉 选择 变异-achieve genetic neural network algorithm is coded cross-choice variant

BP神经网络VC类，此类对BP神经网络进行了封装，整个类是基于动态构建，可以适合于任何采用BP神经网络的模式识别应用。-BP neural network VC categories, such BP neural network to a package, the whole category is based on dynamic construction, and is suitable for use in any BP neural network applications of pattern recognition.

遗传算法的程序和代码，供参考交流-GA procedures and codes, and for information exchange

ID3算法的另一种用java实现的代码，利用向量。-Another ID3 algorithm realize with java code, using vector.

来自于www2.cs.uregina.ca的c4.5源码-from the Bank www2.cs.uregina.ca FOSS

一种新型模糊形态神经网络及其应用研究,比较有参考意义-fuzzy form a new neural network and its applied research, more reference value

多重网格法在step形状区域上的实现,三种不同光滑步可以实现.-Multi-Grid Method in the step shape of the region on the realization of three different smoothing step can be achieved.

Description: C4.5Rule-PANE is a rule learning method which could generate accurate and comprehensible symbolic rules, through regarding a neural network ensemble as a pre-process of a rule inducer. Reference: Z.-H. Zhou and Y. Jiang. Medical diagnosis with C4.5 rule preceded by artificial neural network ensemble. IEEE Transactions on Information Technology in Biomedicine, 2003, vol.7, no.1, pp.37-42. 使用神经网络集成方法诊断糖尿病,肝炎,乳腺癌症的案例研究. -Description: C4.5Rule-PANE is a rule learning method which could generate accurate and comprehensible symbolic rules, through regarding a neural network ensemble as a pre-process of a rule inducer. Reference: Z.-H. Zhou and Y. Jiang. Medical diagnosis with C4.5 rule preceded by artificial neural network ensemble. IEEE Transactions on Information Technology in Biomedicine, 2003, vol.7, no.1, pp.37-42.