搜索资源列表
facedete
- 此程序提取Gabor小波特征，然后由SVM进行分类的Matlab源代码-The Gabor wavelet feature extraction process, then classified by the SVM in Matlab source code
LS-SVM
- 基于LS-SVM的一个预测代码。对实际数值进行预测得到图像-LS-SVM based on a prediction code. Predicted value for the actual image
matlab
- 在matlab环境下编写的支持向量机代码，简单易懂-SVM-code, easy to learn the code for two types of classification
SVM
- 这是一个支持向量机的matlab源代码，可以进行对数据的预测。-This is a support vector machine matlab source code, you can forecast data.
SVM.MATLAB
- SVM matlab 源码和作用 希望大家可以喜欢-SVM matlab source code and the role I hope everyone can enjoy
svm-code
- Matlab code for Support Vector Machine Classification.
SVM
- 基于matlab的支持向量机svm的源代码,可以实现训练及预测的一些基本功能。-Based on support vector machine svm matlab source code, you can achieve some of the basic functions of training and predictable.
SVM
- MATLAB中的SVM源码，用于回归预测，需要的可以下载下-The SVM MATLAB source code for regression forecasting, need can be downloaded below to see the exhibitions
svm(smo)
- svm code in matlab with smo method for optimization
svm-example
- example of svm code in matlab
matlab-svm-tool-box
- 支持向量机用于实现数据挖掘的代码，还有该工具箱的使用实例-matlab code of support vector machine for data mining, with example of this toolbox
SVM
- MATLAB神经网络43个案例分析 第13个案例的源代码及数据集(MATLAB neural network 43 case analysis, thirteenth cases of the source code and data set)
svm
- matlab实现的支持向量机，简易的实现代码学习分享(Matlab support vector machines, simple to achieve code learning to share)
各种分类器matlab程序
- 里面有随机森林，C4.5，ID3，SVM等分类器的matlab代码(There are random forest, C4.5, ID3, SVM classifiers matlab code)
BagSVM-matlab code
- the code is for bag svm in matlab see that.
svm
- matlab code for cbir implimentation
libraries
- svm code using matlab
9、SVM方法
- svm分类器，训练svm的MATLAB代码，简单易理解，好用，能够有效的实现动能(SVM classifier, training SVM MATLAB code, simple and easy to understand, good use, can effectively implement the kinetic energy)
svm
- libsvm回归算法使用源码与数据，使用matlab语言实现(The libsvm regression algorithm uses the source code and the data, and uses the MATLAB language to implement)
svm
- Here is the Matlab code for SVM classification with data.