dlib-ml a machine learning toolkit：dlib毫升的机器学习工具.pdf

Journal of Machine Learning Research 10 (2009) 1755-1758 Submitted 10/08; Revised 4/09; Published 7/09 Dlib-ml: A Machine Learning Toolkit Davis E. King DAVISKING@ USERS. E. NET Northrop Grumman ES, ATR and Image Exploitation Group Baltimore, Maryland, USA Editor:Soeren Sonnenburg Abstract There are many excellent toolkits which provide support fordeveloping machine learning soft- ware in Python, R, Matlab, and similar environments. Dlib-ml is an open source library, targeted at both engineers and research scientists, which aims to provide a similarly rich environment for developing machine learning software in the C++ language. Towards this end, dlib-ml contains an extensible linear algebra toolkit with built in BLAS support. It also houses implementations of algorithms for performing inference in works and kernel-based methods for classi?- cation, regression, clustering, anomaly detection, and feature ranking. To enable easy use of these tools, the entire library has been developed with contract programming, which plete and precise documentation as well as powerful debugging tools. Keywords:kernel-methods, svm, rvm, kernel clustering, C++, works 1. Introduction Dlib-ml is a cross platformopen source software library written in the C++ programming language. Its design is heavily in?uenced by ideas from design by contract ponent-based software engineering. This means it is ?rs