Search - MVU matlab

Search - MVU matlab - List

[Other] MVU DL : 0: 流形学习中的重要方法MVU的源代码，也就是所谓的sde-Manifold learning an important means of MVU
Update : 2025-02-17 Size : 8.22mb Publisher : gxf
[Mathimatics-Numerical algorithms] cca DL : 1: 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-Fei Sha and others prepared CCA manifold learning algorithm of matlab code, which is based on MVU algorithm, but the calculation speed is relatively slow
Update : 2025-02-17 Size : 16kb Publisher : Chenping Hou
[matlab] manifold DL : 0: 基于matlab开发的一个简单的流形学习的工具箱，附带有使用说明-Matlab developed based on a simple manifold learning kit comes with instructions
Update : 2025-02-17 Size : 240kb Publisher : 喻军
[Windows Develop] MVU DL : 0: MVU算法的详细分析，标准的分类算法，高效实现分类-MVU
Update : 2025-02-17 Size : 8.21mb Publisher : anelka
[matlab] lmvu DL : 0: 一个利用半正定规划求解 SDE/MVU 非线性数据降维的算法实现，这是论文原作者提供的 MATLAB 代码。-A MATLAB implementation of the Semi-Definite Embedding (SDE) or namely Maximum Variance Unfolding (MVU) algorithm, provided by the author himself.
Update : 2025-02-17 Size : 17kb Publisher : bsmyht
[matlab] DRTOOL_drtoolbox DL : 0: matlab 降维工具箱，最新版本。包含各类线性及非线性降维代码，lle,lpp,mvu,isomap,npe等皆在其中。-DRTOOL, by itself, creates a new DRTOOL or raises the existing singleton*. H = DRTOOL returns the handle to a new DRTOOL or the handle to the existing singleton*. DRTOOL( CALLBACK ,hObject,eventData,handles,...) calls the local function named CALLBACK in DRTOOL.M with the given input arguments. DRTOOL( Property , Value ,...) creates a new DRTOOL or raises the existing singleton*. Starting from the left, property value pairs are applied to the GUI before drtool_OpeningFunction gets called. An unrecognized property name or invalid value makes property application stop. All inputs are passed to drtool_OpeningFcn via varargin. *See GUI Options on GUIDE s Tools menu. Choose "GUI allows only one instance to run (singleton)".
Update : 2025-02-17 Size : 1.86mb Publisher : lu
[AI-NN-PR] drtoolbox DL : 0: 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 Linear Discriminant Analysis (LDA) Multidimensional scaling (MDS) Isomap Landmark Isomap Local Linear Embedding (LLE) Laplacian Eigenmaps Hessian LLE Local Tangent Space Alignment (LTSA) Conformal Eigenmaps (extension of LLE) Maximum Variance Unfolding (extension of LLE) Landmark MVU (LandmarkMVU) Fast Maximum Variance Unfolding (FastMVU) Kernel PCA Generalized Discriminant Analysis (GDA) Diffusion maps Stochastic Neighbor Embedding (SNE) Symmetric SNE (SymSNE) new: t-Distributed Stochastic Neighbor Embedding (t-SNE) Neighborhood Preserving Embedding (NPE) Locality Preserving Projection (LPP) Linear Local Tangent Space Alignment (LLTSA) Stochastic Proximity Embedding (SPE) Mu
Update : 2025-02-17 Size : 1.94mb Publisher : jdzsj
[Mathimatics-Numerical algorithms] 8095530 DL : 0: 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()
Update : 2025-02-17 Size : 11kb Publisher : weresa
[matlab] matlab DL : 0: 拉普拉斯特征映射,最大差异展开，时频域特征(Laplacian Eigenmap Maximum difference expansion Fast Maximum difference expansion ISOMAP)
Update : 2025-02-17 Size : 8kb Publisher : chen_1001