资源列表
ais
- 人工免疫网络,实现分类,聚类,函数寻优等功能,采用matlab编写.-artificial immune network, classification, clustering, search function Excellence function, prepared using Matlab.
fuzme_matlab
- k-means算法(matlab编写),其中包含测试数据集,可以使用.-This is a k-means algorithm(in matlab) contains data set which can be used
nefcon
- 模糊神经网络采用matlab编程 o install NEFCON follow these steps: 1. Unpack the tar file NEFCON.TAR into your MATLAB working directory: tar xf NEFCON.TAR 2. Start MATLAB 3. Change to the installation directory. 4. Change to the NEFCON directory. 5. Start the STA
GEPAlgorithm
- 基因表达式编程 基本算法 能够完成术用于公式发现、函数挖掘，关联规,则挖掘，因子分解，和预测等-gene expression programming algorithm can be used for the completion of the formula found that function Mining, related regulations, mining, factorization, and the forecast
lvq_KDD_3
- lvq神经网络 的编程 希望大家能用的上-lvq neural network programming hope everyone can be on the
milk-1-0
- MILK 提供了一个实现和比较multi-instance学习算法的环境，基于weka机器学习系统（本站可以下载）-MILK provides a comparison and achieve multi-instance learning algorithm, based on machine learning system weka (site can be downloaded)
tclass-1.0.0
- 用于multivariate时间序列分类，利用了weka机器学习系统（本站可下载）-for multivariate time series classification, the use of machine learning system weka (site available for download)
RSW
- 把 sequential 有导师学习问题转化为传统的有导师学习问题，是weka机器学习系统（本站可下载）的一个拓展-instructors put sequential learning into traditional learning instructors, weka machine learning system (download site), an expansion
CahitArf-src-1.0
- 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
fuzzyWeka_1_0
- 包含FuzzyKMeans, FuzzyGK, FuzzyR等算法，拓展了weka（本站可以下载）-Contains algorithm such as FuzzyKMeans, FuzzyGK, FuzzyR. Extends weka(it is can be download form this site)
绝好原创：vb神经网络原程序
- 请让我成为会员，上串的是我编写的一个诊断专家系统的神经网络部分的代码。-let me become a member, on the string of my preparation of a diagnostic expert system the neural network part of the code.
SVMLight_vc
- 机器学习文本分类的SVM算法实现，VC++ 6.0环境下编译-A SVM algorithm for text classification in machine learning, and compiled under the Visual C++ 6.0 environment.