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Description: Description: S-ISOMAP is a manifold learning algorithm, which is a supervised variant of ISOMAP.
Reference: X. Geng, D.-C. Zhan, and Z.-H. Zhou. Supervised nonlinear dimensionality reduction for visualization and classification. IEEE Transactions on Systems, Man, and Cybernetics - Part B: Cybernetics, 2005, vol.35, no.6, pp.1098-1107.
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Author: 修宇 |
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Description: 一个有监督的非线性能够缩小分类维数的算法源代码
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Size: 30997 |
Author: 钮 吉 |
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Description: mani: MANIfold learning demonstration GUI by Todd Wittman, Department of Mathematics, University of Minnesota E-mail wittman@math.umn.edu with comments & questions.
MANI Website: httP://www.math.umn.edu/~wittman/mani/index.html
Last Modified by GUIDE v2.5 10-Apr-2005 13:28:36
Methods obtained from various authors.
(1) MDS -- Michael Lee
(2) ISOMAP -- J. Tenenbaum, de Silva, & Langford
(3) LLE -- Sam Roweis & Lawrence Saul
(4) Hessian LLE -- D. Donoho & C. Grimes
(5) Laplacian -- M. Belkin & P. Niyogi
(6) Diffusion Map -- R. Coifman & S. Lafon
(7) LTSA -- Zhenyue Zhang & Hongyuan Zha
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Size: 14212 |
Author: suxin |
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Description: Description: S-ISOMAP is a manifold learning algorithm, which is a supervised variant of ISOMAP.
Reference: X. Geng, D.-C. Zhan, and Z.-H. Zhou. Supervised nonlinear dimensionality reduction for visualization and classification. IEEE Transactions on Systems, Man, and Cybernetics - Part B: Cybernetics, 2005, vol.35, no.6, pp.1098-1107.-Description: S-ISOMAP is a manifold learning algorithm, which is a supervised variant of ISOMAP.
Reference: X. Geng, D.-C. Zhan, and Z.-H. Zhou. Supervised nonlinear dimensionality reduction for visualization and classification. IEEE Transactions on Systems, Man, and Cybernetics- Part B: Cybernetics, 2005, vol.35, no.6, pp.1098-1107.
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Size: 31744 |
Author: 修宇 |
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Description: mani: MANIfold learning demonstration GUI by Todd Wittman, Department of Mathematics, University of Minnesota E-mail wittman@math.umn.edu with comments & questions.
MANI Website: httP://www.math.umn.edu/~wittman/mani/index.html
Last Modified by GUIDE v2.5 10-Apr-2005 13:28:36
Methods obtained from various authors.
(1) MDS -- Michael Lee
(2) ISOMAP -- J. Tenenbaum, de Silva, & Langford
(3) LLE -- Sam Roweis & Lawrence Saul
(4) Hessian LLE -- D. Donoho & C. Grimes
(5) Laplacian -- M. Belkin & P. Niyogi
(6) Diffusion Map -- R. Coifman & S. Lafon
(7) LTSA -- Zhenyue Zhang & Hongyuan Zha
-mani: MANIfold learning demonstration GUI by Todd Wittman, Department of Mathematics, University of Minnesota E-mail wittman@math.umn.edu with comments & questions.
MANI Website: httP://www.math.umn.edu/~wittman/mani/index.html
Last Modified by GUIDE v2.5 10-Apr-2005 13:28:36
Methods obtained from various authors.
(1) MDS-- Michael Lee
(2) ISOMAP-- J. Tenenbaum, de Silva, & Langford
(3) LLE-- Sam Roweis & Lawrence Saul
(4) Hessian LLE-- D. Donoho & C. Grimes
(5) Laplacian-- M. Belkin & P. Niyogi
(6) Diffusion Map-- R. Coifman & S. Lafon
(7) LTSA-- Zhenyue Zhang & Hongyuan Zha
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Size: 14336 |
Author: suxin |
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Description: S-ISOMAP is a manifold learning algorithm, which is a supervised variant of ISOMAP.
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Size: 30720 |
Author: wsy |
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Description: 流形学习算法库，包括主要的流形学习算法。LLE，ISOMAP，LE等算法-Manifold learning algorithm library, including the main manifold learning algorithm. LLE, ISOMAP, LE, such as algorithm
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Size: 11010048 |
Author: charles |
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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: In statistics, Isomap is one of several widely used low-dimensional embedding methods, where geodesic distances on a weighted graph are incorporated with the classical scaling (metric multidimensional scaling). Isomap is used for computing a quasi-isometric, low-dimensional embedding of a set of high-dimensional data points. The algorithm provides a simple method for estimating the intrinsic geometry of a data manifold based on a rough estimate of each data point’s neighbors on the manifold. Isomap is highly efficient and generally applicable to a broad range of data sources and dimensionalities.
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Size: 1024 |
Author: Karthikeyan |
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Description: Isomap的改进算法，速度较快。包括了一个瑞士卷生成程序和dijk距离算法。-Improved Isomap algorithm faster. Includes a volume generator and dijk Switzerland distance algorithm.
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Size: 586752 |
Author: 陈普登 |
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Description: :流形学习是一种新的非监督学习方法,近年来引起越来越多机器学习和认知科学工作者的重视. 为了加深
对流形学习的认识和理解,该文由流形学习的拓扑学概念入手,追溯它的发展过程. 在明确流形学习的不同表示方
法后,针对几种主要的流形算法,分析它们各自的优势和不足,然后分别引用Isomap 和LL E 的应用示例. 结果表明,
流形学习较之于传统的线性降维方法,能够有效地发现非线性高维数据的本质维数,利于进行维数约简和数据分
析. 最后对流形学习未来的研究方向做出展望,以期进一步拓展流形学习的应用领域.-As a new unsupervised learning met hod , manifold learning is capt uring increasing interest s of re2
searchers in the field of machine learning and cognitive sciences. To under stand manifold learning bet ter ,
t he topology concept of manifold learning was presented firstly , and t hen it s development history was
t raced. Based on different representations of manifold , several major algorit hms were int roduced , whose
advantages and defect s were pointed out respectively. Af ter that , two kinds of typical applications of Iso2
map and LL E were indicated. The result s show that compared wit h t raditional linear method , manifold
learning can discover t he int rinsic dimensions of nonlinear high2dimensional data effectively , helping re2
searchers to reduce dimensionality and analyze data bet ter . Finally t he prospect of manifold learning was
discussed , so as to extend t he application area of manifold learning.
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Author: 罗朝辉 |
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Description: 基于等距映射( ISOMAP) 非线性降维算法, 提出了一种新的基于用户击键特征的用户身份认证算法, 该算法用测地距离代
替传统的欧氏距离, 作为样本向量之间的距离度量, 在用户击键特征向量空间中挖掘嵌入的低维黎曼流形, 进行用户识别。用采集
到的1 500 个击键模式数据进行实验测试, 结果表明, 该文的算法性能优于现有的同类算法, 其错误拒绝率( FRR) 和错误通过率
( FAR) 分别是1.65 和0 , 低于现有的同类算法。-Based isometric map (ISOMAP) non-linear dimensionality reduction algorithm, we propose a new feature based on the user' s keystrokes the user authentication algorithm with geodesic distance instead of the traditional Euclidean distance between the sample vector as distance measure, the feature vector space in the user' s keystrokes to mine low-Wei Liman embedded manifold, for user identification. 1 with the collected data for 500 Typing Mode experimental test results show that this algorithm outperforms existing similar algorithm, the false rejection rate (FRR) and error through rate (FAR) is 1.65 , respectively, and 0 , lower than existing similar algorithms.
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Author: 罗朝辉 |
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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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Author: lu |
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Description: 线性降维算法的各种论文 包括监督非监督 LLE ISOMAP ROBUST 等-Linear dimensionality reduction algorithms include overseeing various papers unsupervised LLE ISOMAP ROBUST etc.
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Author: 楚博策 |
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Description: Isomap是一种非线性降维方法。又是一种广泛使用的低维嵌入的方法。[ 1 ] Isomap用于计算准等距，低维嵌入的一组高维数据点。该算法提供了一个简单的方法，用于估计基于一个粗略的估计，每个数据点的邻居流形上的数据流形的内在几何。Isomap是高效和一般适用于范围广泛的数据源和维度。-Isomap is a Nonlinear dimensionality reduction method. And is also one of several widely used low-dimensional embedding methods.[1] Isomap is used for computing a quasi-isometric, low-dimensional embedding of a set of high-dimensional data points. The algorithm provides a simple method for estimating the intrinsic geometry of a data manifold based on a rough estimate of each data point’s neighbors on the manifold. Isomap is highly efficient and generally applicable to a broad range of data sources and dimensionalities.
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Size: 8953856 |
Author: liujun |
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Description: Description S-ISOMAP is a manifold learning algorithm, which-The Description of S- ISOMAP is a manifold learning algorithm, which
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Size: 30720 |
Author: pshsb!321603 |
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Description: Description S-ISOMAP is a manifold learning algorithm, which(The Description of S - ISOMAP is a manifold learning algorithm, which)
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Size: 29696 |
Author: Alrxia
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Description: 非线性降维, 使用者必须自己准备数据，可以对立面的参数进行修改(nonlinear dimesion reduction,This package is free for academic usage. You can run it at your own risk.)
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Author: 我是君子兰
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