知道任何好的c++支持向量机(SVM)库?

发布于 2024-08-11 03:53:07 字数 260 浏览 8 评论 0原文

你知道有什么好的 c++ svm 库吗 我尝试了 libsvm http://www.csie.ntu.edu.tw/~cjlin /libsvm/ 但到目前为止我还没有感到惊讶。

我还听说过SVMLightTinySVM。你尝试过吗?有新玩家吗?

谢谢 !

Do you know of any good c++ svm libraries out there
I tried libsvm http://www.csie.ntu.edu.tw/~cjlin/libsvm/ but so far I'm not flabbergasted.

I have also heard of SVMLight and TinySVM. Have you tried them ? Any new players ?

Thanks !

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时光是把杀猪刀 2024-08-18 03:53:07

您可以在此处找到 SVM 库的完整列表。

  • SVMTorch (support vector machines for large-scale regression problems) implemented in the torch machine learning library.
  • mySVM - based on the optimization algorithm of SVM-Light.

A comprehensive list of SVM libraries can be found here.

云之铃。 2024-08-18 03:53:07

我以前使用过SVMLight,发现它非常稳定且快速。我使用它的经历很好并且会推荐它。

然而,我认为关于 SVMLight 的文档可能比 libSVM 少;只是 Thorsten Joachims 的论文和源代码中的注释。一般来说,我并没有发现来源太难理解,但你需要事先阅读论文以了解背景。它也是用纯 C 编写的,而不是 C++,如果这对您很重要的话。

至于“新玩家”,新的研究主要是为了让 SVM 优化算法更加高效。例如,使用随机梯度下降,如 svmsgd飞马。我还没有研究过这些算法的实现,但它是研究代码,所以我不认为它们特别容易遵循,如果这是您最关心的问题。

I've used SVMLight before and found it to be very stable and fast. I had a good experience using it and would recommend it.

However, I think there is probably less documentation on SVMLight than libSVM; just the papers by Thorsten Joachims and the comments in the source code. I didn't find the source too hard to follow in general, but you need to read the papers beforehand to understand the background. It's also written in pure C, not C++, if that matters to you.

As for 'new players', the new research is mostly into making the SVM optimisation algorithms more efficient. For example, using stochastic gradient descent as in svmsgd and pegasos. I haven't looked at the implementations of these algorithms, but it's research code so I wouldn't expect that they are particularly easy to follow, if that's your primary concern.

腻橙味 2024-08-18 03:53:07

最好的入门方法是阅读网站中提供的 libsvm 指南,此外,还可以在此处找到有关如何安装 libsvm 以及执行第一个训练/分类任务的良好入门视频教程:
http://www.youtube.com/watch?v=gePWtNAQcK8
祝你好运,我这几天也刚刚开始,我得到了很好的结果,但仍在调整它。

the best way to get started is to read the libsvm guide provided in the website, also, a good starting video tutorial on how to install libsvm, and do ur first trainig/classification task can be found here:
http://www.youtube.com/watch?v=gePWtNAQcK8
good luck with that, i am also just starting it these days, pretty good results that i got, but still tuning it.

情绪少女 2024-08-18 03:53:07

还有 dlib,它非常完整。

特别是,有用于执行分类、回归、聚类、序列标记、异常检测和特征排名的算法,以及用于进行更专业计算的算法。

There is also dlib, which is quiet complete.

In particular, there are algorithms for performing classification, regression, clustering, sequence labeling, anomaly detection, and feature ranking, as well as algorithms for doing more specialized computations.

一绘本一梦想 2024-08-18 03:53:07

shark

SHARK 是一个模块化 C++ 库,用于自适应系统的设计和优化。它提供了线性和非线性优化的方法,特别是基于进化和梯度的算法、基于内核的学习算法和神经网络,以及各种其他机器学习技术。 SHARK 作为一个工具箱来支持现实世界的应用以及计算智能和机器学习不同领域的研究。这些源与以下平台兼容:Windows、Solaris、MacOS X 和 Linux。

shark

SHARK is a modular C++ library for the design and optimization of adaptive systems. It provides methods for linear and nonlinear optimization, in particular evolutionary and gradient-based algorithms, kernel-based learning algorithms and neural networks, and various other machine learning techniques. SHARK serves as a toolbox to support real world applications as well as research in different domains of computational intelligence and machine learning. The sources are compatible with the following platforms: Windows, Solaris, MacOS X, and Linux.

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