搜索资源列表
PCA_ORL
- Matlab环境下，实现用PCA方法提取EigenFace,之后通过SVM方法对人脸图像进行分类识别。-Face recognition via PCA and SVM method
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- 本程序用pca，kpca,svm,pls,fisher实现cstr和csth过程的故障检诊断，检测率为百分之九十九，故障识别率为百分之九十六-The program use pca, kpca, SVM, PLS, fisher realize CSTR process inspection and CSTH fault diagnosis, detection rate was ninety-nine percent, the fault recognition rate is ninety-
PCAlates
- PCA和SVM的电磁模板分析攻击PCA and SVM for electromagnetic analysis attack templates-PCA and SVM for electromagnetic analysis attack templates
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- 本程序用pca，kpca,svm,pls,fisher实现cstr和csth过程的故障检诊断，检测率为百分之九十九，故障识别率为百分之九十九-The program use pca, kpca, SVM, PLS, fisher realize CSTR process inspection and CSTH fault diagnosis, detection rate was ninety-nine percent, the fault recognition rate is ninety-
Desktop
- The program use pca, kpca, SVM, PLS, fisher realize CSTR process inspection and CSTH fault diagnosis, detection rate was ninety-nine percent, the fault recognition rate is ninety-nine percent-The program use pca, kpca, SVM, PLS, fisher realize CSTR p
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- 本程序用pca，kpca,svm,pls,fisher实现cstr和csth过程的故障检诊断，检测率为百分之九十九，故障识别率为百分之九十七-The program use pca, kpca, SVM, PLS, fisher realize CSTR process inspection and CSTH fault diagnosis, detection rate was ninety-nine percent, the fault recognition rate is ninety-
5
- 本程序用pca，kpca,svm,pls,fisher实现cstr和csth过程的故障检诊断，检测率为百分之九十九，故障识别率为百分之九十五-The program use pca, kpca, SVM, PLS, fisher realize CSTR process inspection and CSTH fault diagnosis, detection rate was ninety-nine percent, the fault recognition rate is ninety-
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- 本程序用pca，kpca,svm,pls,fisher实现cstr和csth过程的故障检诊断，检测率为百分之九十九，故障识别率为百分之九十四-The program use pca, kpca, SVM, PLS, fisher realize CSTR process inspection and CSTH fault diagnosis, detection rate was ninety-nine percent, the fault recognition rate is ninety-
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
svm
- svm工具箱，程序与应用实例 scaleForSVM:归一化 pcaForSVM:pca降为预处理 fasticaForSVM:ica降为预处理 等-svm toolbox, procedures and application examples
SVM
- 支持向量机用于训练和分类，包括PCA降维等函数-Support vector machines for training and classification, including functions such as PCA dimension reduction
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.
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.
machine-learning-ex2-8
- 斯坦福机器学习网上公开课相关编程练习代码，包括线性回归，逻辑回归，神经网络，PCA,SVM等。-the programming code of online course Mechine Learning provided by Stanford.
PCA_SVM face recognition
- relize the idea of the face recognition of PCA-SVM
SVM-KMExample
- examples of SVM, PCA , MultiSVM, Feature extraction, kernel function
基于主分量的人脸重构
- 本实验是基于主成分分析法（PCA）在人脸识别中的应用，采用SVM分类器在ORL人脸库的基础上通过Matlab实现了快速PCA算法的验证仿真。
(PCA+SVM)人脸识别
- 人脸识别，降维 加分类，主成分分析降维，支持向量机分类(Face recognition, principal component analysis reduced Vega classification, dimension reduction, support vector machine classification)
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.)
贝叶斯人脸识别
- Pattern-Recognition-and-Machine-Learning-master,项目包括使用贝叶斯分类器的字符识别，基于GMM的图像分割，使用PCA的人脸识别和具有径向基函数的多类SVM分类器(Pattern-Recognition-and-Machine-Learning-master)