搜索资源列表
MC-SVM1.0.1
- 多类支持向量分类机,可避免两类支持向量分类机的相关缺点,实现多类分类-Multi-Class Support Vector Machine, we can avoid two kinds of support vector machine classification of defects, multi-category classification
01
- 的研究彩色数字图像的计算机分类识别方法并应用于古瓷片的自动分类。方法提出 了一种色彩纹理特征的提取模型,采用该模型,利用IGabor滤波器提取数字图像的色彩纹理特征, 并构造支持向量分类机(SVM)分类器组。结果实现了高准确率多类别图像的自动分类识别,并 成功应用于古瓷片的自动分类。结论色彩纹理特征提取方法将颜色与纹理进行融合,增强了数 字图像之间的特征区分能力。-Study color digital image classification and recognition m
svmnuclass
- 带参数的二次规划支持向量分类机,核函数的用处。-least-square support vector machine classification problem matlab code,functional margin,geometric margin,optimal margin classifier,Kernels feature mapping Regularization and the non-separable case
GGabbor_2dpcca
- Gabor小波提取特征源码,支持向量量机作分类器,能用于掌纹,人脸,指纹识别。-Gabor wavelet feature extraction, and then use the support vector machine as classifier, can be used to palmprint, face, fingerprint identification.
Matlab-libsvm-3.20
- SVM(Support Vector Machine)指的是支持向量机,是常见的一种判别方法。在机器学习领域,是一个有监督的学习模型,通常用来进行模式识别、分类以及回归分析。 Vapnik等人在多年研究统计学习理论基础上对线性分类器提出了另一种设计最佳准则。其原理也从线性可分说起,然后扩展到线性不可分的情况。甚至扩展到使用非线性函数中去,这种分类器被称为支持向量机(Support Vector Machine,简称SVM)。支持向量机的提出有很深的理论背景。 支持向量机方法是在后来提出的
SVM_smo_C++
- 该例程使用C++语言实现,支持向量机的SMO算法,包含标注的数据集,实现13维分类(Implement SVM-SMO algorithm using C++,including training dataset)
svc
- 利用支持向量机方法对不同类别的对象进行分类(use the SVM method to classify)
SVM_GUI_3.1
- 支持向量机实现分类识别,带有图形用户界面,有测试数据以及具体使用说明。(Support vector machine realizes classification and recognition, with graphical user interface, test data and specific instructions.)
GASVM
- 遗传算法优化支持向量机程序,用于参数寻优,提高分类率(Genetic algorithm optimization support vector machine program)
SVM
- SVM(Support Vector Machine)指的是支持向量机,是常见的一种判别方法。在机器学习领域,是一个有监督的学习模型,通常用来进行模式识别、分类以及回归分析。(SVM (Support Vector Machine) refers to support vector machines, which is a common method of discrimination. In the field of machine learning, it is a supervised l
LSSVM
- matlab平台下的最小二乘法支持向量机用于分类,二分类准确率可到100%,三分类可到96%。(The least squares support vector machine under Matlab platform is used for classification. The accuracy of two classification can reach 100%, and three classification can reach 96%.)
Spam-Filter-master
- 垃圾邮件处理,svm支持向量机分类,利用matlab实现,包含垃圾邮件数据(Spam processing, SVM support vector machine classification, using MATLAB, including spam data.)
SVM
- 利用SVM支持向量机进行信号分类,解决非线性信号问题(SVM support vector machine is used to classify signals and solve nonlinear signal problems.)
30个智能算法模型
- 1-8遗传算法,9 多目标Pareto最优解搜索算法,10 基于多目标Pareto的二维背包搜索算法,11-12免疫算法,13-17粒子群算法,18鱼群算法,19-21模拟退火算法,22-24蚁群算法,25-27神经网络,28 支持向量机的分类,29 支持向量机的回归拟合,30 极限学习机的回归拟合及分类(1-8 genetic algorithm, 9 multi-objective Pareto optimal solution search algorithm, 10 multi-obje
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
sklearn-SVM
- 支持向量机(SVM)——分类预测,包括核函数调参,不平衡数据问题,特征降维,网格搜索,管道机制,学习曲线,混淆矩阵,AUC曲线等(Support vector machine (SVM) - classification prediction, including kernel function parameter adjustment, unbalanced data problem, feature dimensionality reduction, grid search, pipelin
最优的TSVM.rar
- 用MATLAB实现半监督支持向量机,可用于分类问题中。(Semi supervised support vector machine is realized by MATLAB, which can be used in classification problems.)
改进svm
- phog方法提取图像特征,svm支持向量机进行分类,分别有GA遗传算法和PSO粒子群优化算法进行寻优。(Phog method extracted image features, SVM support vector machine classification, respectively, GA genetic algorithm and PSO particle swarm optimization algorithm for optimization.)
LSSVM_python_code-master
- 最小二乘支持向量机 ,实现很好的分类效果,零训练误差(Least Squares Support Vector Machines (LSSSMs) to achieve good classification, zero training error)
libsvm-3.25
- libsvm-3.25用于支持向量机多分类