搜索资源列表
libsvm-mat-3.0-1
- 最新的libSVM3.0版本，台湾林智仁团队编写的。-The newest version of livsvm toolbox
gridregression
- 根据libsvm中的grid.py改写的支持向量机回归栅格搜索算法-Grid.py According to rewrite the libsvm Support Vector Machine Regression grid search algorithm
TutorialForFarutoUltimate3.0
- Libsvm-FarutoUltimate3.0，libsvm 加强工具箱使用说明，非常好的pdf文件，另外我将继续上传代码部分。-Libsvm-FarutoUltimate3.0, libsvm strengthen the toolbox for use, very good pdf file, and I will continue to upload the code section.
libsvm-3.0ForClassification
- libsvm contains regression and classification.For those who does not need regression, a package only containing classification is provided in libsvm3.0ForClassification.rar
libsvm3
- 台湾林智仁编写的支持向量机开源程序，可用于分类（C-SVC，nu-SVC，one-class SVM）和回归（epsilon-SVR，nu-SVR）。这是最新版本3.0。-Libsvm3.0 is a simple, easy-to-use, and efficient software for SVM classification and regression. It solves C-SVM classification, nu-SVM classification, one-cla
libsvm-3.1
- libsvm 工具箱 最新版希望对你能用-libsvm toolbox you can use the latest version of hope
libsvm-mat-3.0-1
- 此为台湾大学林智仁教授及所带领的团队编写的关于svm的程序包，简单实用。-This is the National Taiwan University Professor Lin Zhiren and the team led the preparation of the package on the svm, simple and practical.
libsvm-3.1
- 给文件是林贵人博士所开发的c版本支持向量机的源文件，是目前应用最广泛的源程序之一，适用于图像处理，线性拟合，分类等问题。-it is a toolbox of matlab,and the function is used to classify and regression,and so on.
libsvm-3.1
- SVM是一种常用的模式分类机器学习算法，以效率高准确度高闻名于世，libsvm和svmlight是常用的两种SVM实现方法。 这个是台湾林智仁写的，有各种语言版本-SVM is a common pattern classification machine learning algorithm, known to high accuracy, high efficiency, libsvm and svmlight are two commonly used SVM implementation
libsvm3.1java-
- libsvm3.1 java接口版本 可实现分类和回归 实现二分类任务调用训练语句前 采用svm_scale将数据特征值缩放到[-1,1]-classification and regression interface version of libsvm3.1 java achieve to adopt svm_scale before the two-class the task invoked training statement data eigenvalues
java
- 工具libsvm3.14版本的java源码-libsvm3.14 version of java source code
0.5GP0.5S
- 支持向量机，不同核函数的混合来实现图像分割，以libsvm3.1工具箱为基础-Support Vector Machine
0.5PP0.5S
- 基于支持向量机的图像分割，以libsvm3.1工具箱为基础，用不同核函数的混合来实现图像分割，自己编的代码，并以成功运行-Based image segmentation based on support vector machine libsvm3.1 toolbox, with a mix of different kernel functions to achieve image segmentation, their compiled code to run successfully
GS
- 基于支持向量机的图像分割，以libsvm3.1工具箱为基础，用不同核函数的混合来实现图像分割，自己编的代码，并已成功运行-Based image segmentation based on support vector machine libsvm3.1 toolbox, with a mix of different kernel functions to achieve image segmentation, their compiled code to run successfully
PG
- 基于支持向量机的图像分割，以libsvm3.1工具箱为基础，用不同核函数的混合来实现图像分割，自己编的代码，并已成功运行-Based image segmentation based on support vector machine libsvm3.1 toolbox, with a mix of different kernel functions to achieve image segmentation, compiled code, and has been successfully
PS
- 基于支持向量机的图像分割，以libsvm3.1工具箱为基础，用不同核函数的混合来实现图像分割，自己编的代码，并已成功运行-Based image segmentation based on support vector machine libsvm3.1 toolbox, with a mix of different kernel functions to achieve image segmentation, compiled code, and has been successfully
libsvm-svdd-3.17
- svm svdd3.17版本，配套libsvm3.17最新版本-svm svdd3.17 version, the latest version supporting libsvm3.17
WekaUse
- Weka各类分类器的使用（Java）.MyEclipse2013+Weka3.6+libsvm3.18+Jdk1.7+Win8.1-Weka various types of classifiers using (Java). MyEclipse2013+Weka3.6+libsvm3.18+Jdk1.7+Win8.1
libsvm-3.1-[FarutoUltimate3.1Mcode]
- libsvm3.1-farutoUltimate版本.1.基于目前的最新的libsvm-3.1编写。 2.对原来的部分代码进行了重新优化。 3.添加ClassResult.m函数，方便给出各种分类准确率，以及给出判别函数的权值w、偏置b、支持向量在原始训练集中的位置索引以及alpha系数。-libsvm3.1-farutoUltimate version .1. Based on current latest libsvm-3.1 compilation. 2. The original
libsvm-3.20-(2)
- libsvm3-20源码注释,适合初学者学习libsvm-libsvm code