LIBSVM is an integrated software for support vector classification, (C-SVC, nu-SVC), regression (epsilon-SVR, nu-SVR) and distribution estimation (one-class SVM). It supports multi-class …

A typical use of LIBSVM involves two steps: first, training a data set to obtain a model and second, using the model to predict information of a testing data set. For SVC and SVR, …

Instructions for using LIBSVM are in the README files in the main directory and some sub-directories. README in the main directory: details all options, data format, and library calls. …

small number of features via LIBSVM [19]. We use OpenSSL 1 as our encryption tool, which is open-source and designed originally for the SSL/TLS protocol implementation. The random …

Download LIBSVM MATLAB interface from LIBSVM page and build it. Download plotroc.m to the main directory of LIBSVM MALTAB interface. Type > help plotroc to get usage and examples. …

This page contains many classification, regression, multi-label and string data sets stored in LIBSVM format. For some sets raw materials (e.g., original texts) are also available. These …

The new release (version 2.0) of LIBSVM is an integrated tool for support vector classification, regression as well as two varients: nu-SVM and one-class SVM. All these different problems …

This page contains many classification, regression, multi-label and string data sets stored in LIBSVM format. For some sets raw materials (e.g., original texts) are also available. These …

Instead of seeking a very fast software for difficult problems, we provide a simple, easy-to-use, and moderately efficient software for SVM classification: LIBSVM. It is a simplification of both …

到此我已經簡單的說明了 libsvm 的使用方式， 更完整的用法請參考 libsvm 的說明跟 cjlin 的網站、 SVM 的相關文件，或是去上 cjlin 的課。 Here we have already briefly explained the libsvm …