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recommender-
- Collaborative Filtering，基于Collaborative Filtering，建立主动为用户推荐商品的推荐系统。实现参考协同过滤算法或它的优化，实现并改进算法，计算出每个客户对未购买的商品的兴趣度，并向客户主动推荐他最感兴趣的N个商品。实验数据可以从MovieLens.com下载。要求使用至少10，000不同用户的数据，至少1000个不同的movie。-Collaborative Filtering，Based Collaborative Filtering, the in
k_clique
- [X,Y,Z] = k_clique(k,A) Inputs: k - clique size A - adjacency matrix Outputs: X - detected communities Y - all cliques (i.e. complete subgraphs that are not parts of larger complete subgraphs) Z - k-clique matrix-k-clique alg
DataMiningFPGrowth
- FP-Growth算法的java实现，简单易于理解。经测试，可用。不过不能输出关联规则。-FP-Growth algorithm to achieve the java, simple and easy to understand. Tested and available. But not output association rules.
DataMiningApriori
- apriori的java实现，写的有点长，不能输出关联规则。经测试，可用。-apriori achieve the java, write a bit long, you can not output association rules. Tested and available.
FP-Growth
- fp-growth算法的c++实现，比较简单，但不能生成关联规则。-fp-growth algorithm c++ implementation, relatively simple, but can not generate association rules.
SVM-intrduction
- svm支持向量机的基础导论，纯理论学习，没有附带源码-Introduction to support vector machines svm basis, purely theoretical study, does not come with source code
BIRCH-Algorithm
- 本代码是关于数据挖掘的层次聚类算法的编程实例，请勿用于商业用途上-The code is the programming examples on data mining hierarchical clustering algorithm, not for commercial use
JBIRCH
- 本代码是关于数据挖掘的层次聚类算法的java编程实例，请勿用于商业用途上-The code is java programming examples on data mining hierarchical clustering algorithm, not for commercial use
JBIRCH-src
- 本代码是关于数据挖掘的层次聚类算法的JAVA编程实例，请勿用于商业用途上-The code is JAVA programming examples on data mining hierarchical clustering algorithm, not for commercial use
heston-summer-xls
- GAUSS has two electronic help systems, corresponding to the GAUSS pdf manuals (available at http://www.aptech.com). 1. The Command Reference is an easy way to pick up information on commands (as long as they are not deemed obsolete ), and is or
multiverso-master
- Multiverso is a parameter server based framework for training machine learning models on big data with numbers of machines. It is currently a standard C++ library and provides a series of friendly programming interfaces. With such easy-to-use APIs, m
gplvm
- 这是一个用于高斯过程隐变量模型的工具箱，其中包含了MATLAB/C/PYTHON三种语言版本-As of July 2005 a C++ implementation of the GPLVM exists which has most of the flexibility of this software but runs much faster. However as of this time it cannot handle very large data sets as the spar
P1-s2.0-S0957417410001107-main
- Business cycle predictions face various sources of uncertainty and imprecision. The uncertainty is usually linguistically determined by the beliefs of decision makers. Thus, the fuzzy set theory is ideally suited to depict vague and uncertain feature
GSP
- GSP是基于apriori思想的高效序列模式挖掘算法，不用二次遍历所有序列集。-GSP is based on highly efficient sequential pattern mining algorithm apriori thought, do not traverse all secondary sequence set.
DataTest
- 统计一亿个IP中每个出现的次数，找不到大数据之类的分类，只能选择数据挖掘-Statistics IP in one hundred million times each appears, can not find such a large data classification, data mining can only choose
LDA-topic-model
- 首先声明，这是别人写的LDA主题模型代码，本人测试过，可以运行，但是输出跟输出有点不尽人意，输入的是词的序号和该词在文档中出现的次数，要是可以直接读取文档就完美了。输出是主题以及词在该主题出现的概率，其中得到的主题我就看不懂了，不知道是算法问题，还是因为我的水平有限。在研究LDA主题模型的朋友，可以下载试一下-First statement, which is written by someone else LDA topic model code, I tested, you can run,
NaiveBayesClassifier.m
- I use Matlab 2008a which does not support Naive Bayes Classifier. scr ipt supports normal and kernel distributions. Statistics toolbox for 2008a version is used in the scr ipt. Also includes function for confusionmat
k_meansPP
- K-means++算法是K-means算法的一个改进算法，其中主要改进了k值的选取不会在影响聚类的效果，具有高度的自动性-K-means++ algorithm K-means algorithm, an improved algorithm, in which the major improvements k value does not affect the clustering effect, a high degree of automaticity
Maltab
- 文件里面是数据挖掘中各种经典算法的MATLAB的源代码，尤其适合不只懂原理不会写代码的人进行数据建模- The document is a variety of data mining algorithms in the classic MATLAB source code, especially for people who do not understand the principle of not only the code to write data modeling
simpleMKL
- 多核学习之simpleMKL工具箱，里面包含了simpleMKL算法和MKL-wrapper算法，其中原始工具箱中MKL-wrapper不能运行，此处已进行了修正。-Multi-core learning simpleMKL toolbox, containing the simpleMKL algorithm and MKL- wrapper algorithm, the original toolbox MKL- wrapper can not run, has been revised.