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Semi-supervised Discriminant Analysis
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Discriminant analysis
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数据挖掘的线性判别分析,用matlab编写-Data Mining linear discriminant analysis, using matlab write
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LINEAR DISCRIMINANT ANALYSIS - A BRIEF TUTORIAL-LINEAR DISCRIMINANT ANALYSIS- A BRIEF TUTORIAL
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Canonical Discriminant Analysis is a dimension-reduction technique related to PCA and CCA
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AR人脸库进行DCT变换,然后使用Fisher discriminant analysis 进行特征提取,使用cos分类器进行人脸分类。-AR Face Database for DCT transform, and then use the Fisher discriminant analysis feature extraction, using cos classifier for human face classification.
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在ar人脸库上使用鉴别公共向量方法(discriminant common vector)方法实现人脸图像鉴别分析-In the ar face database using the identification of public-vector method (discriminant common vector) method of achieving facial image discriminant analysis
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编程是由pca和lda结合的脸部特征提取,用于三维图像。-multilinear principal component analysis combined with Linear discriminant analysis 3D face feature extraction.
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This file represents Cline Specific linear discriminiant based on linear discriminant analysis.
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article about PCA algorithm
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In this paper, we show how support vector machine (SVM) can be
employed as a powerful tool for $k$-nearest neighbor (kNN)
classifier. A novel multi-class dimensionality reduction approach,
Discriminant Analysis via Support Vectors (SVDA), is in
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Discriminant Analysis Toolbox
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FISHER线性鉴别分析的理论研究及其应用.PDF-FISHER linear discriminant analysis theory and its applications. PDF
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Face Recognition by Fisher and Scatter Linear Discriminant Analysis.rar
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特征提取是模式识别研究领域的一个热点.本文提出了一种基于独立成分分析和线性鉴别分析的特征提取方法.谊方法中引入了零空间的概念,指出了前人算法中的不足之,并且给出了一个完整的独立成分分析和线性鉴别分析的组合算法.在ORL和Yale人脸数据库上的实验表明了该方法的有效性.-Feature extraction is a hot field of pattern recognition research. In this paper, which is based on independent com
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摘要:主成分分析(PCA)的人脸识别算法,以减少的特征向量是涉及到对抽象的特点,改进了主成分分析(一)iUumination算法的变化影响酶原sed.The方法是基于上减低与正常化其相应的标准差的特征向量元素相关联的大特征值的特征向量的影响力的想法。耶鲁大学和耶鲁大学面临的数据库面对数据库B是用来验证-Abstract:In principal component analysis(PCA)algorithms for face recognition,to reduce the influen
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线性判别分析(LDA)是一种较为普遍的用于特征提取的线性分类方法。但是将LDA直接用于人脸识别
会遇到维数问题和“小样本”问题。人们经过研究,通过多种途径解决了这两个问题并实现了基于I,DA的人脸识
别 文章对几种基于LDA的人脸识别方法做了理论上的比较和实验数据的支持,这些方法包括Eigenfaces、Fish—
erfaceS、DLDA、VDLDA及VDFLDA。实验结果表明VDFLDA是其中最好的一种方法。-Low—dimensional feature representat
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Integrating Independent Components and Linear Discriminant Analysis
for Gender Classification
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人脸识别文章 Uncorrelated Discriminant Nearest Feature Line Analysis for Face Recognition-Face article Uncorrelated Discriminant Nearest Feature Line Analysis for Face Recognition
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贝叶斯优化在线性判别分析中的应用,这是国外一个大牛写的程序,很有价值-This code is an implementation of the method Bayes Optimal Discriminant Analysis
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