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libsvm-2.88.rar
- LIBSVM 是台湾大学林智仁 (Chih-Jen Lin) 博士等开发设计的一个操作简单、易于使用、快速有效的通用 SVM 软件包，可以解决分类问题（包括 C- SVC 、n - SVC ）、回归问题（包括 e - SVR 、 n - SVR ）以及分布估计（ one-class-SVM ）等问题，提供了线性、多项式、径向基和 S 形函数四种常用的核函数供选择，可以有效地解决多类问题、交叉验证选择参数、对不平衡样本加权、多类问题的概率估计等。,LIBSVM is林智仁Taiwan Univ
SVM-classifier
- 用matlab实现非线性支持向量机分类器对多类进行分类。-Using matlab to achieve non-linear support vector machine classifier for multi-class classification.
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
2445
- 基于支持向量聚类的多聚焦图像融合算法∗ Exploiting SVC Algorithm for Multifocus Image Fusion-Based on support vector clustering algorithm for multi-focus image fusion
oao
- 多分类问题的支持向量机源程序一对一方法 绝对可以运行-Multi-class SVM using One-Against-One decompositionoao
FaceDe
- 基于支持向量聚类的多聚焦图像融合算法. 从无监督机器学习角度提出了一种基于SVC(support vector clustering)的图像融合规则,解决了基于 SVM(support vector machine)的融合规则在处理多聚焦图像融合问题时所引起的区域混叠与非平滑过渡问题,进一步提高了融合图像的质量.-Based on support vector clustering algorithm for multi-focus image fusion. Never oversig
20090501SleepingKoala
- 所上传文件包包括6种vc++源代码：使用opencv的实现可视图的静态路径规划；简单的svm算法；基于vc2008的图像匹配（多工程结构）；基于局部搜索的K-means聚类算法；三维匹配中的ICP算法；视觉tracking中的condensation算法-Upload file package, including the six kinds of vc++ source code: using opencv to view the realization of the static path
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
libsvm-2.89
- 是一種線性方成的分類器。SVM透過統計的方式將雜亂的資料以NN的方式分成兩類，以便處理。LIBLINEAR is a linear classifier for data with millions of instances and features. It supports L2-regularized logistic regression (LR), L2-loss linear SVM, and L1-loss linear SVM. -Main features of LIBLINEA
demosvm
- matlab编写的svm实现多类分类的源代码，训练算法包括OAA算法、OAO 算法、BSVM2算法等。-matlab prepared svm multi-category classification of the source code, training algorithms, including OAA algorithm, OAO algorithm, BSVM2 algorithm.
Multi-classSVMClassifierUtilizingBinaryDecisionTre
- 有关svm 多类的问题，用二叉树来解决的。一篇英文。可以参考。-The svm multi-class problems, and use a binary tree to be resolved. One in English. Can refer to.
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
- In this paper, we show how support vector machine (SVM) can be employed as a powerful tool for $k$-nearest neighbor (kNN) classifier. A novel multi-class dimensionality reduction approach, Discriminant Analysis via Support Vectors (SVDA), is in
SPIDER_mclass
- Multi-class Coding (adapted from from LS-SVM for SPIDER). Encode (code_MOC, code_ECOC, code_OneVsAll, code_OneVsOns) and decode (codedist_hamming, codedist_bay) a multi-class classification task into multiple binary classifiers.
svm-light
- svm分类的算法 速度比其他的快一点 需要再做比较 交流 希望能得到更多的资料-SVMmulticlass uses the multi-class formulation described in [1], but optimizes it with an algorithm that is very fast in the linear case
PCA-feature-extraction-and-SV-multi-class
- PCA特征抽取与SVM多类分类在传感器故障诊断中的应用PCA feature extraction and SVM multi-class classification in the sensor fault diagnosis-PCA feature extraction and SVM multi-class classification in the sensor fault diagnosis
SVM-hssvm1.0.1
- HSSVM是一个用超球SVM（Hyper-Sphere Support Vector Machines）模型求解多分类问题的工具包，采用Java语言实现。开发该程序的主要目的，是利用超球SVM求解模型代替传统上借助于解二分类问题的经典SVM模型来求解多分类问题。本文将论述该程序的主要实现细节，包括相关算法及设计原理的描述。-HSSVM is an ultra ball SVM (Hyper-Sphere Support Vector Machines) to solve multi-classi
000
- 支持向量机(svM)是一种新的机器学习技术。本文采用一对一方法构建多分类SVM 分类器。利用常用的灰度共生矩阵方法提取图像纹理特征，组成特征向量，输入构建好的SVM 多分类器中进行分类。对从Brodatz纹理库中选取的4张纹理图像进行了分类实验，取得较好的 分类结果-Support vector machine (svM) is a new machine learning techniques. In this paper, one way to build a multi-cla
Recognition-activities-using-SVM
- 利用Support Vector Machine來處理對影像辨識，能判斷影像所傑取到的人是處於何種動作之下，最後並比較多種分類器之結果-Recognition of human activities using SVM multi-class classifi er,including used o-v-o,o-v-a,DAGSVM and SVM-BTA to compare.