搜索资源列表
lle
- 局部线性嵌入,是一种流行学习的算法,可以学习任意维数的低维流形-locally linear embedding is a algorithm of manifold learning, it can be used to learn arbitrary dimension of low dimensional manifold
MultiPCA
- 多流形PCA是学习多流形的基础,能够帮助理解多流形过程!-The more manifold PCA is learning the basis of multi-manifolds, manifold process can help understand!
SDEmatlab
- 基于监督学习的一种非线性数据降维方法,可以很好地将低维特征从其所在的高维流形中提取出来,用于数据分类。-A nonlinear data dimension reduction based on supervised learning method, is a good way to the lower dimensional feature extracted from its place of higher dimensional manifold, used for data classi
MONOPOLY
- 模拟网上流形的放大富豪游戏,涉及到堆栈,映射等各种STL容器,是学习数据结构的一次好的练习-Simulate manifold magnification rich game online
lpp
- 局部保持投影算法,机器学习中流形算法,L-Locality preserving projection algorithms, machine learning algorithms flowing shape, LPP
16-node-manifold-element
- 用于计算薄板弯曲的16节点数值流形法,值得学习-16-node manifold element for thin plate-bending analysis
Sparse-Embedding
- 该代码matlab所编写,实现稀疏流形子空间嵌入,可直接运行,对稀疏编码的相关学习有帮肋-The code is written matlab realize sparse subspace manifold embedding, can be run directly on the sparse coding related learning help rib
a
- 流形自适应学习算法,能时间在Matlab上运行,并包含参考文献。(the program running on the Matlab platform.)
KLPP
- 核局部邻域嵌入算法是一类流形学习算法,可用于数据的降维(Kernel local neighborhood embedding algorithm is a manifold learning algorithm, which can be used to reduce the dimensionality of data)
UDP
- UDP算法是一种基于流形学习的无监督降维算法,可以用来提取特征和可视化分析。(UDP algorithm is an unsupervised dimensionality reduction algorithm based on manifold learning, which can be used to extract features and visual analysis.)
dxfqxdw
- ISOMAP算法,包括dfun m dijk m isomap m l2_distance m等等等等,一种流形学习算法很好用,()
26755458lle
- 流形学习中常见的lle算法,不仅可以运行,还可以实现可视化(The common LLE algorithm in manifold learning can not only run, but also can be visualized.)
8095530
- Fei Sha 等人编写的流形学习算法CCA的matlab代码,它基于MVU算法,但是计算速度比较慢()
30631009
- ISOMAP算法,包括dfun m dijk m isomap m l2_distance m等等等等,一种流形学习算法很好用,()
ifmpg
- 一种流形学习算法(很好用),主要是基于mtlab的程序,关于非线性离散系统辨识。( A fluid manifold learning algorithm (good use), Mainly based on the mtlab procedures, Nonlinear discrete system identification.)