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基于matlab平台的libsvm,用于分类和回归-Based on matlab platform libsvm, for classification and regression
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基于GPU计算的SVM,VC++源码,包括详细文档说明文件。借用了GPU编程的优势,该代码据作者说比常规的libsvm等算法包的训练速度快13-73倍,预测速度快22-172倍。希望对大家有用-cuSVM is a software package for high-speed (Gaussian-kernelized) Support Vector Machine training and prediction that exploits the massively parallel proc
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libsvm-mat-2.9-1用于分数据回归、分类、预测等数据分析功能- MATLAB codes of support vector machine svm classification, regression yuce deng
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SVM light 工具箱 包含window版本和matlab版本
由美国cornell大学的教授Thorsten Joachims部署
执行SVM二分类
速度明显快于libsvm
下载文件中包含
1.例子(inductive SVM 和 transductive SVM)
2.说明文件
3.源程序-SVM light kit (including window version and matlab version)
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这是matlab编写的Logistic Discrimination 和 KNN分类器代码。这两个算法的实现参考了《Introduction to Machine Learning》。 除此在代码中还包含了调用matlab自带的libsvm的例程。rumLogisticDiscrimination, runKnn, runSvm分别对这3个算法在数据集liver_train_data上的分类准确度进行测试。测试结果在code report.doc 中有简要描述。-This code implem
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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
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能快速的使用lssvm去做多分类和回归,能高效的调用matlab函数库-Can quickly use classification and regression libsvm do more to efficiently call matlab function library
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基于SVM的分类程序,基于台湾的LIBsvm改编的,里面有指导怎么运行,能够编译。-SVM-based classification program that can run it
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SVM工具箱,matlab环境下进行故障特征值分类识别的有效工具-SVM toolbox, effective tool for fault classification were eigenvalues matlab environment
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libsvm matlab code for classification of remote sensing data
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How to install the libsvm for MATLAB on Unix machine
Linear-kernel SVM for binary classification
kernel SVM for binary classification
cross validation for C and Gamma
multi-class SVM: one-vs-rest (OVR)
More ready-to-use matlab example
Ava
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The following is a matlab code using LIBSVM for loan classification, using german credit dataset and text classification using LIBSVM
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二分类,参数寻优 matlab 支持向量机(Two classification)
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随着科学技术的飞速发展,机器学习与人工智能技术的不断创新,人们对特定信息检索的需求逐渐增加,使得如何对资源进行合理有效的分类成为一个关键问题。近几年来,基于内容的图像分类的研究焦点主要集中在自然图像的场景分类和物体分类两个方面,大多采用有监督学习方法,通过对底层特征建模和中间语义分析来实现分类。
本文基于Libsvm的图像分类研究及实现,主要针对的是物体分类这一方面,选用了五类水果作为分类研究的对象。对图像进行分类的大体步骤主要包括采集图像样本(主要从Web上获取)、图像预处理(如截成大小一致
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libsvm 在matlab 中的应用之多分类预测问题方法一对多(One of many ways to apply libsvm to matlab in multi-classification prediction problem)
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Libsvm is a simple, easy-to-use, and efficient software for SVM
classification and regression. It solves C-SVM classification, nu-SVM
classification, one-class-SVM, epsilon-SVM regression, and nu-SVM
regression. It also provides an automatic model
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