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模式识别PCA+LDA的C++源代码,用于图像的主分量分析-pattern recognition PCA LDA C source code for the image of Principal Component Analysis
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这里面包含两个文件,可以实现主成分分析(PCA)算法和线性判别分析(LDA)算法。不过还需要CMatrix类的定义。-which contained two documents, can be achieved principal component analysis (PCA) algorithm and linear discriminant analysis (LDA) algorithm. But also need CMatrix class definition.
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应用PCA(主成分分析)进行人脸识别的matlab程序,有较高成功率-PCA (Principal Component Analysis) face recognition Matlab procedures, which have a higher success rate
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PCA and PLS aims:to get some
insight into the bilinear factor models Principal Component Analysis
(PCA) and Partial Least Squares (PLS) regression, focusing on the
mathematics and numerical aspects rather than how s and why s of
data analysis
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pca人脸识别This package implements basic Principal Component Analysis in Matlab and
tests is with grayscale portion of the FERET database. Images are not
preprocessed and it is up to the user to preprocess the images as wanted,
not changing the fil
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C语言编写的PCA程序,实现主成分分析功能-C language of the PCA program to achieve the principal component analysis function
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该程序包实现了模式识别中的两个特征提取算法,主成分分析PCA和线性判别分析LDA。采用C++语言编写,开发环境VS。 程序包还提供了两个测试样本文件。-The package to achieve the recognition of the two feature extraction algorithm, principal component analysis PCA and linear discriminant analysis LDA. Using C++ language, dev
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This toolbox includes routines for using principal component analysis (PCA) and independent component analysis (ICA) to extract cellular signals from imaging data sets. A full descr iption and validation of the method is provided in the paper, "Autom
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pca主成分分析,matlab程序,用于图像特征提取,降维等
有中文注释-Principal component analysis
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PCA_face_recognition,使用主成分分析PCA的方法进行人脸识别-PCA_face_recognition, using principal component analysis PCA method for face recognition
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本篇文章提供了一些对于主成分分析法matlab源码分析解释,简单,中文解释。-This article provides some of the principal component analysis for matlab source code analysis and interpretation, simple Chinese explanation.
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主成分分析法实现特征选择,里面有非常详细的算法介绍,还有一个现实实例介绍,非常具象,里面贴有实现算法的matlab代码-Principal component analysis (PCA)to achieve feature selection , which has a very detailed descr iption of algorithms , there is a real example to illustrate , very concrete , which is affix
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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
Lin
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斯坦福大学深度学习,PCA主成分分析的补充完的代码-PCA principal component analysis of deep learning at Stanford, added the code
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机器学习算法,利用PCA来简化数据,降维技术,主成分分析-Machine learning algorithm, using PCA to simplify data dimensionality reduction techniques, principal component analysis
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感知行为的影响因素包括单个关节的动作和不同关节的组态。因此提出一种新的基于关节的位置差异的特征类型,联合包括静态姿势、动作、位移在内的行为信息进行识别。采用关节在两个时间和空间区域的差异来明确地模拟个别关节动力学和不同关节的组态。然后应用主成分分析(PCA)来获得所需的特征。同时应用非参数的简捷的贝叶斯最近邻(NBNN)分类器进行多类行为的分类。这个NBNN分类器避免了帧描述符的量化,计算“图像到类别”的距离而不是“图像到图像”的距离。15到20帧的数据就足以实现手势以及动作的识别,无需应用整个
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pca主成分分析,在多变量选择上效果较好,对数据的主成分进行分析,常用于分类、聚类、实验数据处理-Pca principal component analysis in multivariate selection effect is good, principal component analysis of data, often used in classification, clustering, experimental data processing
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Principal Component Analysis
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主成分分析,空间降维的人工智能算法,也能用来去相关性,在图像等信号处理常用-Principal component analysis, spatial dimensionality reduction of artificial intelligence algorithms, but also can come and relevance, in the image signal processing such as common
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PCA及whiten算法MATLAB实现,Principal Component Analysis,主成分分析,白化-PCA and whiten algorithm MATLAB realize, Principal Component Analysis, Principal Component Analysis, albino
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