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 classification. The basic algorithm is a simplification of both SMO by Platt and SVMLight by Joachims. It is also a simplification of the modification 2 of SMO by Keerthi et al. Our goal is to help users from other fields to easily use SVM as a tool. LIBSVM provides a simple interface where users can easily link it with their own programs. Main features of LIBSVM include Different SVM formulations Efficient multi-class classification Cross validation for model selection Weighted SVM for unbalanced data Both C++ and Java sources GUI demonstrating SVM classification and regression