搜索资源列表
Radial-basis-function
- 径向基函数是一个取值仅仅依赖于离原点距离的实值函数，也就是Φ（x）=Φ(‖x‖),或者还可以是到任意一点c的距离，c点称为中心点，也就是 Φ（x，c）=Φ(‖x-c‖)。任意一个满足Φ（x）=Φ(‖x‖)特性的函数Φ都叫做径向量函数，标准的一般使用欧氏距离，尽管其他距离函数也是可以的。一些径向函数代表性的用到近似给定的函数，这种近似可以被解释成一个简单的神经网络，径向基函数在支持向量机中也被用做核函数。-Radial basis function depends only on the valu
csvm
- 在支持向量机中，用c-svm解决不可分问题-In support vector machine, with the c-svm solve the problem can not be separated
libsvm-mat-2.89-3
- 支持向量机,C++与Matlab，测试可通过-Support Vector Machine
SVM-code
- 支持向量机源代码，用C语言编写的，适用于分类及回归分析-Support vector machine (SVM) source code, written in C language, suitable for classification and regression analysis
svmtrain
- 支持向量机训练函数代码文件，C语言编写，实用小巧-SVM training function code files, C language, practical compact SVM training function, C language
remote-sense1
- 遥感影像的英文论文，支持向量机，模糊C均值，挺有用的-Remote sensing image of English papers, support vector machine (SVM), a fuzzy c-means, very useful
CPPAlgorithm-Design
- 大部分科研领域的模式识别算法都是在MATLAB中实现，此处提供了个别模式识别算法的C++语言实现，如支持向量机，遗传算法等。-Most of the field of pattern recognition algorithm was implemented in MATLAB, individual pattern recognition algorithm is provided here of the C++ language, such as support vector machine
SVM-soft-border
- 支持向量机，类别为软边界，用C语言编写而成-Support vector machines, the category is soft borders, written by visual C
libsvm-3.20
- 同时用C和matlab是实现的支持向量机原码，请详细阅读dex.txt(如何使用)-While C and matlab realize SVM original code, please read dex.txt (how to use)
SVMcgForClass
- 用于支持向量机的惩罚参数和G的参数寻优问题，利用网格算法的搜索方式，并进行了可视化-we try to find the most optimal c and g to get the highest accuracy base SVM
libsvm
- 支持向量机的（包括核的使用）c++实现。-support vector machine by c++
GLCM
- Jurkat和Ramos两类细胞光学衍射图像特征提取和分类；Visual C++语言；通用模块使用；支持向量机。-Jurkat and Ramos cells optical diffraction image feature extraction and classification Visual c++ language General module USES Support vector machine (SVM).
Genetic-algorithm-to-optimize-svm
- 遗传算法优化支持向量机的惩罚系数C与高斯核系数g，能够提高支持向量机的分类精度-Genetic algorithm to optimize the punish coefficient of support vector machine (SVM) with gaussian kernel coefficient C g, can improve the support vector machine (SVM) classification accuracy
SVMtest
- 经测试数据验证 可以实现支持向量机的分类，该算法使用C++编写-Verified by the test data of support vector machine (SVM) classification, the algorithm using c++
SVMcgForClass
- svm(支持向量机)对于分类问题网格参数优化（c，g） -svm grid for best c and g
svm-matlab-
- 支持向量机的源代码，可以实现分类和回归分析。-ctions on Intelligent Systems and Technology ABSTRACT LIBSVM is a library for Support Vector Machines (SVMs). We have been actively developing this package since the year 2000. The goal is to help users to easily apply SVM t
SVMcg
- 该程序是支持向量机搜寻最佳-c和-g的函数，一般能使分类器的识别率提高几个百分点。-The program is the support vector machine search for the best-c and-g function, generally can improve the recognition rate of a few percentage points.
libsvm-mat
- 关于支持向量机的源代码，以及C源代码实现-SVM source code
winsvm
- C++编写的支持向量机完整代码，含测试、训练数据集。-Written in C++ support vector machine complete code
DeepLearnToolbox_CNN_lzbV2.0
- DeepLearnToolbox_CNN_lzbV2.0 深度学习,卷积神经网络,Matlab工具箱 参考文献: [1] Notes on Convolutional Neural Networks. Jake Bouvrie. 2006 [2] Gradient-Based Learning Applied to Document Recognition. Yann LeCun. 1998 [3] https://github.com/rasmusberg