这是一个用于数据挖掘的常用算法的模板库（数据挖掘的C++模板库for UNIX)...

利用vb控制乐高机器人-use vb robot control Sealock

java神经网络工具箱-neural network toolbox

一个bp神经元网络的c++实现，优化了算法，有可执行界面-A bp neural network c++ to achieve and optimize the algorithm, there is an executable interface

数据挖掘c45分类算法 数据挖掘c45分类算法-C45 data mining data mining classification algorithms C45 classification algorithm

矩形件排样优化问题是一个多目标优化问题，另一方面要考虑到生产时的下料效率-Rectangular pieces of nesting optimization problem is a multi-objective optimization problem, on the other hand, taking into account the production efficiency of the next expected

用遗传算法求解TSP问题。。。matlab编写，并附带有城市坐标用于检验。-Genetic Algorithm for TSP with the problem. . . matlab prepared, together with the coordinates with the city for inspection.

LIBSVM源码。LIBSVM 是台湾大学林智仁(Chih-Jen Lin)博士等开发设计的一个操作简单、 易于使用、快速有效的通用SVM 软件包，可以解决分类问题（包括C- SVC、 n - SVC ）、回归问题（包括e - SVR、n - SVR ）以及分布估计（one-class-SVM ） 等问题，提供了线性、多项式、径向基和S形函数四种常用的核函数供选择，可以有效地解决多类问题、交叉验证选择参数、对不平衡样本加权、多类问题的概率估计等。-LIBSVM source. LIBSVM is林智仁Taiwan University (Chih-Jen Lin) Dr. develop design a simple, easy to use, fast and effective generic SVM software package, can solve the classification problems (including the C-SVC, n- SVC), regression ( including e- SVR, n- SVR) as well as the distribution of estimates (one-class-SVM) and so on, provides a linear, polynomial, radial basis function and the S-shaped kernel function of four commonly used for selection, can effectively to solve a wide range of issues, cross-validation to choose the parameters of the imbalance in the weighted sample, multi-category probability estimation.

将遗传算法(GA)与传统SVM算法结合,构造出一种参数最优的进化SVM(GA2SVM),SVM 模型采用径向基函数(RBF)作为核函数，利用格雷码编码方式对SVM算法的模型参数进行遗传编码和优化搜索，将搜索到的优化结果作为SVM 的最终模型参数。-Genetic algorithm (GA) combined with the traditional SVM algorithm, a kind of tectonic evolution of the optimal parameters of SVM (GA2SVM), SVM model using Radial Basis Function (RBF) as kernel function, the use of Gray code encoding algorithm of the SVM model parameters of genetic coding and optimization of search, will search for the optimal results as the final SVM model parameters.

关联规则并行算法Count Distribution的C与MPI实现-Parallel Algorithm for Association Rules Count Distribution of C and MPI realize

遗传算法强制交叉算法-GA mandatory cross-Algorithm