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MushroomClassification
- opencv实现的mushroom数据的分类，一共有八种不同的学习方法，包括贝叶斯、SVM、神经网络，等等。-opencv implementation mushroom data classification, a total of eight kinds of different learning methods, including Bayesian, SVM, neural networks, and so on.
learcode
- 行人检测源程序，居于svm技术。和梯度直方图提取-Pedestrian Detection source, living in SVM technology. And gradient histogram extraction
2DLDAwiththeSVM-basedfacerecognitionalgorithm
- 二维线性鉴别分析(2DLDA)算法能有效解决线性鉴别分析(LDA)算法的“小样本”效应，支持向量机 (SVM)具有结构风险最小化的特点，将两者结合起来用于人脸识别。首先，利用小波变换获取人脸图像的低频分量，忽 略高频分量：然后，用2DLDA算法提取人脸图像低频分量的线性鉴别特征，用“一对多”的SVM 多类分类算法完成人脸 识别。基于ORL人脸数据库和Yale人脸数据库的实验结果验证了2DLDA+SVM算法应用于人脸识别的有效性。-”Small sample size”problem
svm
- opencv实现的svm算法的代码示范，可用于学习svm的原理和使用效果。-opencv svm algorithm implementation code demonstration svm can be used to learn the principles and results.
svm_-linear_unseparable
- opencv实现的svm，对标准svm原理做了基本的改进，能够处理线性不可分的情况。-opencv realized svm, svm standard basic principle made improvements to handle the case of non-linear.
BOF_SVM
- Bag of Feature and SVM example using opencv
libSVM-opencv
- 使用opencv实现SVM，测试样例是三种不同的花，具有不一样的花瓣长度等参数-Using opencv achieve SVM, test samples are three different flowers, with petals of different parameters such as length
SVM
- 自己用opencv实现的机器学习十大算法中的支持向量机算法，经过测试，算法运行很好-Own opencv realize with the machine learning ten algorithms in support vector machine algorithm, tested, the algorithm runs very well
INRIAHogLbpLabel
- 本方法是hog+lbp+svm来判断是否为行人，函数库为opencv，代码为C++，hog是opencv自带的，lbp为均匀模式，59维度，训练样本为INRIA数据集-opencv lbp svm president detection inria data