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Description: 一个用来计算高维数据线性图形嵌入的matlab函数，是几乎所有线性降维算法（如LPP, NPE, IsoProjection, LSDA.）都要用的一个文件，在这里上传给大家，一定用得着！
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Size: 2868 |
Author: ttt |
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Description: 一个用来计算高维数据线性图形嵌入的matlab函数，是几乎所有线性降维算法（如LPP, NPE, IsoProjection, LSDA.）都要用的一个文件，在这里上传给大家，一定用得着！-A high dimensional data used to calculate the linear graphics embedded matlab function, is that almost all linear dimensionality reduction algorithms (such as LPP, NPE, IsoProjection, LSDA.) Should be used in a document From here to the U.S., we use gained!
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Size: 3072 |
Author: ttt |
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Description: 流形学习算法lle的线性化方法，是一种非监督的降维方法，比lle的优势在于可以将新的样本点映射到低维空间。-Lle manifold learning algorithm of the linearization method, is a non-supervised dimensionality reduction method has the advantage of being more than lle can sample the new point is mapped to the low-dimensional space.
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Size: 2048 |
Author: 仲国强 |
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Description: 本代码实现基于成对约束的半监督图嵌入算法-Following the intuition that the image variation of
faces can be effectively modeled by low dimensional
linear spaces, we propose a novel linear subspace
learning method for face analysis in the framework of
graph embedding model, called Semi-supervised
Graph Embedding (SGE). This algorithm builds an
adjacency graph which can best respect the geometry
structure inferred from the must-link pairwise
constraints, which specify a pair of instances belong to
the same class. The projections are obtained by
preserving such a graph structure. Using the notion of
graph Laplacian, SGE has a closed solution of an
eigen-problem of some specific Laplacian matrix and
therefore it is quite efficient. Experimental results on
Yale standard face database demonstrate the
effectiveness of our proposed algorithm.
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Size: 2048 |
Author: 刘国胜 |
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Description: 人脸识别的子空间方法，包括LLE，ISOMAP和NPE等维数约减算法-Subspace method for face recognition, including LLE, ISOMAP and NPE dimensionality reduction algorithm such as
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Size: 174080 |
Author: 韩静书 |
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Description: 维数约减matlab工具箱，包括LLE，ISOMAP，NPE等，具有较好的效果-Dimensionality reduction matlab toolbox, including LLE, ISOMAP, NPE, etc., with good results
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Size: 936960 |
Author: 韩静书 |
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Description: 程序为matlab代码，LGM是NPE调用的-Procedures for the matlab code, LGM is called NPE
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Size: 5120 |
Author: 储敏 |
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Description: 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)".
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Size: 1952768 |
Author: lu |
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Description: 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
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Size: 2029568 |
Author: jdzsj |
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Description: 最新最强MATLAB降维工具箱，可用于人脸识别，模式识别，机器学习，数据挖掘，图像处理等领域，里面包含的算法有PCA,LDA,KPCA,KLDA,Laplacian，LPP,MDS,NPE,SPE,LLC,CFA,MCML,LM-The latest and greatest dimension reduction MATLAB toolbox can be used for face recognition, pattern recognition, machine learning, data mining, and other areas of image processing, which contains the algorithm PCA, LDA, KPCA, KLDA, Laplacian, LPP, MDS, NPE, SPE, LLC, CFA, MCML, LMNN etc.
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Size: 1042432 |
Author: FDX |
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