搜索资源列表
Classification-MatLab-Toolbox
- 模式识别matlab工具箱,包括SVM,ICA,PCA,NN等等模式识别算法,很有参考价值-pattern recognition Matlab toolbox, including SVM, ICA, PCA, NN pattern recognition algorithms, and so on, of great reference value
1087
- pca+svm源代码（matlab） matlab代码，pca进行特征提取，svm进行分类
stprtool.rar
- 统计模式识别工具箱（Statistical Pattern Recognition Toolbox）包含： 1，Analysis of linear discriminant function 2，Feature extraction: Linear Discriminant Analysis 3，Probability distribution estimation and clustering 4，Support Vector and other Kernel Machines,
PCA_SVM.rar
- 此方法采用经典的PCA对人脸图像进行特征提取，用libsvm库函数的SVM分类器对图像分类。,This method uses the classical PCA on the face image feature extraction, with the libsvm library function of SVM classifier for image classification.
prtools3.1.7.rar
- 模式识别 MATLAB 的工具箱,比较实用,包括SVM,ICA,PCA,NN等等模式识别算法.,Pattern Recognition Toolbox for MATLAB, more practical, including the SVM, ICA, PCA, NN pattern recognition algorithm and so on.
stprtool15aug08
- 捷克理工大学Hlavac教授和Franc博士提供的统计模式识别Matlab工具箱的最新版本V2.09，在原有版本基础上进行了一些修改和完善。它包括现有模式识别的大部分方法，比如SVM，PCA，LDA等。我采用其中的SVM方法进行了人体下肢假肢SEMG信号的分类，效果不错。希望能对大家有帮助。-Statistical Pattern Recognition Toolbox for Matlab (C) 1999-2008, Version 2.09. It includs a number of
kpca
- 使用核PcA来识别图片，图片为200张测试图片，200张训练图片，包含在在压缩文件中。-To identify the use of nuclear PcA picture, pictures, for 200 test images, 200 training images, is included in the compressed file.
PCA-(ICA)
- 主成分分析程序包，包括主成分分析和独立主成分分析两个程序源代码。-Principal component analysis package, including principal component analysis principal component analysis and independent source code for both procedures.
ToolBox
- matlab图像处理工具相，使用了主成分分析，ANN，SVM等方法。-This toolBox used in the image processing(feature extraction and classification) PCA,LDA,ICA,DCT,RBF,RBE,GRNN,KNN,minimum distance,SVM, and others
chapter13
- 《数字图像处理与机器视觉:Visual C++与Matlab实现》6 支持向量机,综合案例——基于PCA和SVM的人脸识别系统-" Digital image processing and machine vision: Visual C++ and Matlab to achieve" 6 support vector machines, comprehensive case- based on PCA and SVM for Face Recognition Syste
knnPcaWithGA
- In this code I have used GA in supervised PCA to find the best coeficients for overall covariance. the classification is made by K-In this code I have used GA in supervised PCA to find the best coeficients for overall covariance. the classification i
KPCA
- 在ORL或Yale标准人脸数据库上完成模式识别任务。用PCA与基于核的PCA（KPCA）方法完成人脸图像的重构与识别试验. -Or Yale in the ORL face database, complete the standard pattern recognition tasks. With the PCA and kernel-based PCA (KPCA) method to complete the reconstruction of face image and reco
matlab-face-detection
- pca+svm 与pca +adaboost 人脸检测，里面包含有程序的详细说明-pca+svm, pca+adaboost people face detection, which contains a detailed descr iption of the program
code-PCA-SVM
- 这是一个包含PCA降维的matlab程序加上用svm分类的一个程序。-This is a PCA dimensionality reduction plus matlab program contains a program with svm classification.
face
- Matlab PCA+SVM人脸识别,通过PCA和SVM算法达到人脸识别的功能。-Matlab PCA+SVM，To identify people s face.
SVM
- 支持向量机SVM和核函数的MATLAB程序集,用于图形处理的算法，分类算法-pca and svm use MATLAB
Classification-MatLab-Toolbox
- 模式分类工具箱，有PCA、SVM、ID3源代码，用于数据分析、模式识别和机器视觉。-Pattern classification toolbox, there PCA, SVM, ID3 source code for data analysis, pattern recognition and machine vision.
FaceRec_SourceCode
- 基于PCA-SVM的人脸识别，平均识别率达83 ，是基于matlab开发的。-PCA-SVM-based face recognition, the average recognition rate of 83 , based on matlab development.
matlab
- 用于脑电信号分析的matlab算法，对数据进行PCA处理及SVM分类。(The matlab algorithm for EEG signal analysis performs PCA processing and SVM classification on data.)
基于PCA的SVM分类
- 选择“BreastCancer”数据集，使用支持向量机(SVM)对其进行分类。作为对比，第一次对特征集直接进行支持向量机分类，第二次对特征集进行主成分分析法的特征提取后，再对特征提取后的特征集进行支持向量机分类。并且对比和分析了两次分类的结果。(The BreastCancer data set is selected and classified by Support Vector Machine (SVM). For comparison, the first time the featur