搜索资源列表
drtoolbox
- Matlab针对各种数据预处理的降维方法，源码集合。-Currently, the Matlab Toolbox for Dimensionality Reduction contains the following techniques: Principal Component Analysis (PCA) Probabilistic PCA Factor Analysis (FA) Sammon mapping Lin
bhtsne-master
- 实现bh_tsne算法 支持windows Linux OSX平台 可使用C++ Matlab Python运行(Barnes-Hut t-SNE suport WindowsOS LinuxOS OSX you can you it through Matlab and Python and C++)
Random_Forest
- 内涵PCA降维;SMOTE插值;t-SNE降维等算法的随机森林算法，以及鸢尾花数据集，有利于新手或者工程性实验借鉴~(Connotative PCA dimensionality reduction; SMOTE interpolation; t-SNE dimensionality reduction algorithms such as random forest algorithm, as well as iris data sets, is conducive to novice or
tSNE_function_matlab
- t-SNE function。点开即用，封装完好方便，逻辑清晰。t-SNE降维(t-SNE function. It is easy to use and the logic is clear. T-SNE dimensionality reduction)
tsne_python
- T-SNE高维数据降维特征提取，用于python3(T-SNE demensinal,python)
MATLAB数据处理代码
- 34种数据降维方法代码；分段线性插值算法代码；基于RPCA异常值检测代码；基于t-sne算法的降维可视化实例；基于埃尔米特插值多项式代码；基于二维数据内插值代码...
基于t-SNE降维的学生成绩聚类模型
- 使用Python编写的小程序代码，基于t-SNE降维的学生成绩聚类模型。(Clustering model of students' performance based on t-sne dimension reduction)