Training linear SVMs in linear time

著者: Thorsten Joachims - ACM SIGKDD Conference on Knowledge Discovery and Data Mining 2006 被引用: 1,961

Linear Support Vector Machines (SVMs) have become one of the most prominent machine learning techniques for high-dimensional sparse data commonly encountered in applications like text classification, word-sense disambiguation, and drug design. These applications involve a large number of examples n as well as a large number of features N, while each example has only s