搜索资源列表
PCA-SVM
- 在PYTHON里面，采用LIBSVM，实现对TE数据的多类故障的分类。-In PYTHON inside, using LIBSVM, TE data to realize the classification of many types of failures.
PCA
- 对输入的高维特征向量进行pca降维后输出低维的特征向量-PCA dimensionality reduction
pca
- PCA主元分析后用神经网络预测，A/S含量，PCA算法实现，与神经网络-PCA principal component analysis using neural network prediction, A/S content, PCA algorithm, and neural network
pca-svm
- 使用pca和svm方法对表情进行分类，有较高的识别准确率-The use of pca and expression svm classification methods, which have a higher recognition accuracy
pca-svm
- pca的matlab实现,very good-achievement of pca with matlab
pca(ica)svm
- 基 于 pca(ica)-svm 实 现 故 障 诊 断 -PCA_test.......
PCA
- Principal component analysis,for study about classification data,develop for svm , lvq etc-Principal component analysis,for study about classification data,develop for svm , lvq etc
mathpro
- pca+ svm source code (matlab) matlab code, pca for feature extraction, svm classification
PCA-SVM
- 人脸识别程序 程序源代码可见 识别精度高PCA-SVM-Face Recognition program PCA-SVM
pcasvm1
- 这是一篇关于PCA/SVM的人脸识别论文并附有我编的源码-This is an paper on PCA/SVM for face recognition papers including my source code
svm
- SVM分类器 分类各种图片的类别 分类各种图片的类别 -SVM classifiers various pictures of various categories of classification of classified images of various image types
pca-svm
- 基于pca的人脸识别程序，人脸库需要自己下载，供参考-Pca-based face recognition program needs to download face database, for reference
Yale_5G
- Yale,PCA,SVM,matlab,人脸检测,特征提取,人脸识别.-Yale, PCA, SVM, matlab, face detection, feature extraction, face recognition.
gabor-pca
- 本程序是先用gabor小波变换对人脸图像处理，然后在用pca进行降维，最后用svm分类器进行多分类分类识别，包扩完整的orl人脸库，需注意的是，svm工具箱是用的libsvm工具箱，运行前先配置好libsvm。版本号：libsvm-mat-2[1].89-3[FarutoUltimate3.0]-This procedure is to use the human face gabor wavelet transform image processing, and then to reduce
PCA-and-SVM-Face-recognition
- 采用PCA对人脸特征进行抽取，用SVM多累分类器对人脸进行识别，有操作界面-Using PCA for facial feature extraction, and more tired with the SVM classifier for face identification, a user interface
PCA-SVM
- 利用PCA-SVM的图片降维和识别分类，并分析重建误差等的主程序-The use of PCA-SVM pictures dimensionality reduction and identification and classification, and analyze the main reconstruction error, etc.
PCA-SVM-master
- PCA/SVM算法实现图像分类，分类准确率可到达90%(Image classification by PCA/SVM algorithm)
PCA+SVM
- 用于人脸识别，包含了PCA及SVM算法，数据集采用的ORL数据库(face recognition(PCA+SVM))
PCA+SVM
- 先用PCA降维，在利用支持向量机进行分类，这个分类是二分类，所以PCA的降维降到两维即可分类。(Firstly, PCA dimensionality reduction is used to conduct classification with support vector machine. This classification is binary classification, so the dimensionality reduction of PCA can be reduced t
PCA+SVM的人脸识别
- 使用pca和svm的方法对人脸进行识别和检测，最终达到人脸识别的功能(Face recognition and detection using PCA and SVM methods, and finally achieve the function of face recognition)