资源列表
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.
kmeans
- 利用了matlab编程，结果实现k-means算法-Use matlab programming, k-means algorithm to achieve results. . .
GUI-toolbar-and-tips
- GUI工具栏及其使用技巧，这里给了两个具体实例和其中一个画图过程。-GUI toolbar and tips, here to give two concrete examples and one drawing.
arima
- ARMA,AR,MA,ARIMA等实现自回归预测、齐次稳定回归预测算法-ARMA, AR, MA, ARIMA, etc. to achieve autoregressive prediction, homogeneous and stable regression prediction algorithm
R-language-packages
- R语言常用计量包，初学者可以使用这个查找自己要用的包。-R language package
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
Data-dimensionality-reduction
- 该压缩文件为部分数据降维方法，有LTSA、HHLLE、ISOMAP、LLTSA、LLP-The compressed file for the partial data dimensionality reduction method, there are LTSA, HHLLE, ISOMAP, LLTSA, LLP
programs-and-data
- 通过KNN分类法，根据酒的某些性状信息对酒进行分类。然后，通过交叉验证对分类结果进行测试。最后，对数据进行主成分分析，再进行分类。-By KNN classification, according to certain traits information wine wine classification. Then, through cross-validation of the classification tested. Finally, principal component analy
日常运动数据分析
- 用anaconda内部的科学库进行分析运动数据，并能对数据进行分类。(Anaconda's internal science library is used to analyze the motion data and to classify the data.)
Tensor-Factorization-HOSVD-iterative-master
- hosvd 迭代分解,很好用，是一个硕士论文里的代码(terative HOSVD algorithm to decompose tensor and find its Singular factors in each mode.)
dpp
- 通过行列式点过程，可以选取高质量，高多样性的特征(High quality, high diversity features can be selected)
kmediod
- k-mediod、knn、uci数据集。 数据挖掘、机器学习中的经典聚类、分类算法(K-mediod, KNN, and UCI data sets. Data mining and classical clustering and classification algorithms in machine learning)