A Library for Support Vector Machines | |
LIBSVM | |
Developer: | Chih-Chung Chang and Chih-Jen Lin |
Latest Release Version: | 3.3 |
Operating System: | Cross-platform |
Programming Language: | Java, C++ |
Genre: | Machine Learning |
License: | BSD |
LIBSVM and LIBLINEAR are two popular open source machine learning libraries, both developed at the National Taiwan University and both written in C++ though with a C API. LIBSVM implements the sequential minimal optimization (SMO) algorithm for kernelized support vector machines (SVMs), supporting classification and regression.[1] LIBLINEAR implements linear SVMs and logistic regression models trained using a coordinate descent algorithm.[2]
The SVM learning code from both libraries is often reused in other open source machine learning toolkits, including GATE, KNIME, Orange[3] and scikit-learn.[4] Bindings and ports exist for programming languages such as Java, MATLAB, R, Julia, and Python. It is available in e1071 library in R and scikit-learn in Python.
Both libraries are free software released under the 3-clause BSD license.[5] [6]