SSTCA

实现通用的matlab蚁群算法的c++源码 重复使用度高()

说明：  boxcox函数的python实现，引用该函数可将偏态分布调整为正态分布(Python implementation of box Cox function)

用EM算法求解高斯混合模型并可视化，数据是男女生的身高分布，前提是初始化男女生身高各自的均值和方差和比例，然后由EM算法求解，男女生身高的均值方差，以拟合数据。(The EM algorithm is used to solve the Gauss mixture model and visualize. The data is the height distribution of male and female. The premise is to initialize the mean, variance and proportion of the male and female height, then the mean variance of the height of male and female is solved by the EM algorithm, so as to fit the data.)

说明：  分类器的性能比较与调优: 使用scikit-learn 包中的tree，贝叶斯，knn，对数据进行模型训练，尽量了解其原理及运用。 使用不同分析三种分类器在实验中的性能比较，分析它们的特点。 本实验采用的数据集为house与segment。(Performance comparison and optimization of classifiers: We use tree, Bayesian and KNN in scikit-learnpackage to train the data model and try to understand its principle and application. The performances of three classifiers are compared and their characteristics are analyzed. The data set used in this experiment is house and segment.)

说明：  R语言构建贝叶斯网络，很实用的讲解和案例(Construction of Bayesian network with R language, a very practical explanation and case)

数据挖掘经典算法，频繁项集挖掘经典算法，TWOPHASE算法，源码中有详细注释

说明：  粗糙集在进行属性约简时需要求其正域，此为求正域程序(Rough Set for Positive Domain)

这段代码是层次聚类的Matlab实现代码( This code is hierarchical clustering Matlab implementation code)

主要内容为R语言环境下的社交网络数据挖掘，附有源代码和数据，并包含案例所使用的PPT和相关文献。(The main content is under R locales social network data mining, with the source code and data, and includes cases PPT and related documentation used.)

一种神经网络算法：极限学习机（ELM)，包括分类和回归，仿真验证无误，适合初学者练习(A data mining algorithm: limit learning machine (ELM), including classification and regression, simulation verification is unmistakable, suitable for beginners to practice)