搜索资源列表
toolbox_tensor_voting.zip
- 张量投票在matlab环境下的仿真。球型张量及棒型张量的仿真,Tensor voting in matlab simulation environment. Spherical and rod-type tensor tensor Simulation
motorimage_Csp
- 脑电想象运动的csp特征提取分类算法 matlab平台，通过投票可以直接扩展到多类-Imagine the movement csp EEG feature extraction classification algorithm matlab platform, through the vote can be directly extended to multiple classes
TVF
- 根据Medioni的张量投票理论，用matlab实现二维图像的重构。-According Medioni s tensor voting theory, with the realization of two-dimensional image reconstruction of matlab.
Ensemble
- 用adaboost算法生成基支持向量机分类器，并对识别结果进行简单投票法集成。附有支持向量机工具箱和adaboost算法流程说明。-Adaboost algorithm to generate the base with a support vector machine classifier, and the recognition result is a simple voting method integration. With support vector machine algorith
naive-bayes-classifier
- 程序实现了naive bayes classifier， 并附有对美国参议院根据投票情况来判断议员属于民主党还是共和党的例子。-Program achieved a naive bayes classifier, along with the U.S. Senate voting to determine under Democrat and Republican members belonging examples.
read_dot_edge_file
- 张量投票算法中生成张量场的相关函数，其中包括对图像的取向估计和二阶张量的生成-Tensor voting algorithm to generate the correlation function tensor field, including the orientation of the image is estimated to generate second-order tensor
FisherMultiClassDiscri
- 基于Fisher准则多分类特征提取，投影后采用最近邻算法和一对一投票法进行分类和交叉验证，附上数据实例-After feature extraction based on Fisher criterion with multicalsses, the projections are discriminated ultilizing the nearest neighbor algorithm and one-versus-one ballot to have a cross validation
Hough1
- hough,霍夫变换直线提取线性规划直线，包括投票空间-The hough, the hough transform line, the linear programming line, including the polling space
Majority-Vote-function-for-Matlab--master
- 使用matlab实现多数投票，可用于高光谱图像处理(a way of majority voting using matlab)
Active Learning Literature Survey
- 系统地讲解了主动学习的方法，QBC算法，投票熵等等(The methods of active learning, QBC algorithm, voting entropy and so on are systematically explained)
libsvm-mat-2[1].89-3[FarutoUltimate3.0Mcode]
- 一般的支持向量机只支持二分类，使用libsvm可以实现多分类，原理也是基于二分类，然后在使用投票机制，经测验，libsvm的分类精度可达85%以上(Multi class supported by libsvm,after testing, the classification accuracy can reach 85%.)