搜索资源列表
kpca_toy
- 基于核主成分分析方法设计的分类器 分类器可用于对非线性数据分类非原创- Kernel PCA non linear class
PCA-ICA
- 实现了主元分析（PCA）和独立分量分析（ICA）相关信号处理。非线性降维。(Implements Principal Component Analysis (PCA) and Independent Component Analysis (ICA) correlation signal. Non-linear dimension reduction using kernel PCA.)
kernelpca_tutorial
- 在信号处理技术中，使用PCA非线性降维。(Non-linear dimension reduction using kernel PCA.)
kernel_eca-master
- Kernel Entropy Component Analysis,KECA方法的作者R. Jenssen自己写的MATLAB代码，文章发表在2010年5月的IEEE TPAMI上面-Kernel Entropy Component Analysis, by R. Jenssen, published in IEEE TPAMI 2010.(We introduce kernel entropy component analysis (kernel ECA) as a new method fo
SVM_Mdl.mat
- These files are matlab source code for price forecasting for smart meter hourly data. Step 1 relevant features are selected by Gray Correlation, Random Forest, Relief F algorithms. Then Kernel PCA of features are calculated. Price is predicted by Ker
KECA_Journal_Article
- Robert Jenssen 撰写论文原文(We introduce kernel entropy component analysis (kernel ECA) as a new method for data transformation and dimensionality reduction. Kernel ECA reveals structure relating to the Renyi entropy of the input space data set, estimated