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基于matlab的SVM三分类算法
- SVM的多分类问题，在matlab平台下的源代码分析。
bsvm-2.06
- 台湾林智仁等开发的用于SVM多分类软件，包括一对多SVM、一对一SVM、DAGSVM等算法的实现-Taiwan' s Lin Zhiren, etc. for the development of SVM multi-classification software, including one to many SVM, one-SVM, DAGSVM such as Algorithm
Matlab-m-SVM-code
- 这是我在网上找了很久的多分类支持向量机matlab代码，欢迎交流！-This is my search on the net for a long time many classification support vector machine matlab code, welcome exchanges!
libsvm-mat-2[1].89-3
- svm多分类器，包括多分类和GA算法和PSO算法优化的SVM-svm multi-classifier, including the multi-classification and GA algorithm and PSO algorithm for optimization of SVM
3class_svm_matlab
- 使用libsvm进行三分类，svm多分类可以类似编程-Use libsvm for three categories, svm classification can be more similar to programming
svm
- 这是在模式识别中常用的一个分类器，不过这是一个线性2分类问题，对于多分类问题，可以直接转化~-This is commonly used in pattern recognition, a classifier, but this is a linear 2 classification for multi-classification problems, can be directly translated into
non-linearSVMmulti-classification
- 转发一个可视化的非线性支持向量机多分类源码，比较实用易学，值得进一步深入开发。-non-linear SVM multi-classification
multi-classSVM
- 总结SVM多分类的文章，从训练时间、分类时间、分类器的个数等等入手进行对比-Summary SVM multi-classification of articles, from the training time, classification time, the number of classifiers, and so begin to compare
SVM
- 这个是svm的一遍小论文 比较好 基于模糊核聚类的svm多类分类方法-svm
SVM
- SVM(支持向量机)，二分类，多分类，多分类一对一，多分类一对多训练及测试matlab代码-SVM two classes muticlasses mutioneagainstone mutioneagainstall matlab code
svm
- svm 可以实现多分类 希望对你能有帮助-svm classification can achieve more than you want to help
ensembles_pca_svm_new10v
- pca做特征降维，然后进行特征空间随机分割构造多个svm分类器，并行处理，对样本进行分类，基于特征空间的svm多分类器-using pca reduce feature dimension,split feature space and then randomly divided over svm classifier construction, parallel processing, the samples were classified, based on multi-feature sp
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
svm
- 支持向量机由Vapnik首先提出，像多层感知器网络和径向基函数网络一样，支持向量机可用于模式分类和非线性回归，该程序主要实现svm的分类和回归功能。(SVM was first proposed by Vapnik. Like multilayer sensor network and radial basis function network, SVM can be used for pattern classification and non-linear regression. The p
wine
- SVM多分类算法，基于svmlib适合初学者学习(SVM multi classification algorithm, based on svmlib suitable for beginners to learn)
Sample4
- 支持svm多分类，运算时间较长，支持svm多分类的matlab代码，精度不高。(Support svm multi-classification)
19107matlab自编svm
- 利用原算法adaboost弱学习器基于决策树桩的方法对样本数据进行多分类(Multi-classification of sample data based on decision tree stump using AdaBoost weak learner)
svm多分类
- 用于svm多分类，值得学习，可以尝试运行，修改后使用。
SVM 多分类
- 通过一对多，和多对一的方式，将二分类svm转化成多分类分类器(Through the way of one to many and many to one, the two classification SVM is transformed into a multi classification classifier)
逻辑回归
- 根据标签，完成SVM下的多分类数据识别，数据可以是字符或者信号，可以达到较高的识别精度(The multi-classification data recognition under SVM was completed)