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statslibrary's Introduction

statslibrary

统计分析与机器学习课程实验作业

statslibrary包含主成分分析,聚类分析等统计分析算法的实现。

需要使用某个算法模块,只需要包含对应模块文件夹下的对应头文件即可使用,各个模块的使用说明文档也请参见对应的文件夹下的readme文档。statslibrary中所实现的各个分析算法请参见如下的目录。

目录

1. Distance:距离计算模块,包含欧氏距离,马氏距离等距离计算方法

2. CorreCoef:相关系数与相关系数矩阵计算模块,包含pearman相关系数,spearman相关系数等相关系数计算方法

3. GeneralStats:一般分析统计量计算模块,包含平均数,中位数,众数,分位数,方差,标准差,极差,偏度,峰度等统计量计算方法

4. VarAnaly:方差分析模块,包含单因素方差分析和双因素方差分析

5. *LinearRegre:回归分析模块,包含一元和多元线性回归分析

6. PCA:主成分分析模块

7. Kmeans:K-Means, Kmeans聚类法模块

8. SCM (Ward-Hierarchical-Clustering):系统聚类法(又称层次聚类法)模块

9. DistanceDiscri:距离判别分析模块

10. BayesDiscri:朴素贝叶斯判别分析模块

11. *FisherDiscri:费歇判别分析模块

12. FacAnaly:因子分析模块

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