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这是一个应用了线性鉴别分析方法的程序，供大家参考学习-This is an application of the linear discriminant analysis procedures, for your reference study
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局部线性判别分析 用于半监督降维 下载于作者主页-Local Linear discriminant analysis for semi-supervised dimensionality reduction downloaded the author' s home
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Linear Discriminant analysis
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Face recognition written in MATLAB. This code implements Fisher s Discriminant Analysis and SVMs using LIBSVM.-The motivation of this project is to implement several techniques for face recognition:
Principal Component Analysis
Fisher’s Linear
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线性判别分析LDA降维算法，类内距离最小，类间距离最大，训练、测试、分类完整的处理流程-Linear discriminant analysis LDA dimensionality reduction algorithm, the smallest within-class distance, the maximum distance between the classes, training, testing, processing complete classification
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模式分类之fisher线性判别分析,对已知数据进行分类处理。-fisher linear discriminant analysis of pattern classification, known data classification.
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matlab平台实现人脸识别，通过PCA降维后再通过线性判别分析LDA实现人脸匹配。内附ORL人脸数据库，运行main函数即可输出结果-Matlab platform to achieve face recognition, PCA dimensionality reduction and then through linear discriminant analysis LDA face matching. Contains ORL face , run the main function t
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k最近邻法、有权重的k最近邻法及线性判别-K-nearest neighbor and linear discriminant analysis
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Dimensionality reduction is one of the important preprocessing
steps to handle high-dimensional data. Linear discriminant
analysis (LDA) is a classical and popular approach for this purpose.
LDA finds an optimal linear transformation, which max
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ldatrace performs Linear Discriminant Analysis with optional-Ldatrace performs Linear Discriminant Analysis with optional
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ldatrace performs Linear Discriminant Analysis with optional-Ldatrace performs Linear Discriminant Analysis with optional
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ldatrace performs Linear Discriminant Analysis with optional-Ldatrace performs Linear Discriminant Analysis with optional
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Its linear discriminant analysis
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ldatrace performs Linear Discriminant Analysis with optional(Ldatrace performs Linear Discriminant Analysis with optional)
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性判别式分析(Linear Discriminant Analysis, LDA)，也叫做 Fisher 线性判别
(FisherLinear Discriminant,FLD)， 是模式识别的经典算法(Linear Discriminant Analysis)
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本文件提供了核线性判别分析（KLDA）的将维算法(This program is the kernel linear discriminant analysis)
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线性判别式分析，可以用来对数据进行分类或数据降维（不同于PCA）(Linear discriminant analysis)
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LDA算法 将带上标签的数据（点），通过投影的方法，投影到维度更低的空间中，使得投影后的点，会形成按类别区分，一簇一簇的情况，相同类别的点，将会在投影后的空间中更接近。(Linear Discriminant Analysis)
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2D线性判别分析工具箱，该方法为Pattern recognition letters关于2DLDA的源码(2D linear discriminant analysis toolbox, which is the source code for Pattern recognition letters on 2DLDA)
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LDA的一篇介绍。 LDA的全称是Linear Discriminant Analysis（线性判别分析），是一种supervised learning。LDA是在目前机器学习、数据挖掘领域经典且热门的一个算法(An introduction to LDA. LDA's full name is Linear Discriminant Analysis (Linear Discriminant Analysis), is a supervised learning. LDA is a clas
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