Support vector machines Export

@article{citeulike:820314, abstract = {My first exposure to Support Vector Machines came this spring when I heard Sue Dumais present impressive results on text categorization using this analysis technique. This issue's collection of essays should help familiarize our readers with this interesting new racehorse in the Machine Learning stable. Bernhard Sch\"{o}lkopf, in an introductory overview, points out that a particular advantage of SVMs over other learning algorithms is that it can be analyzed theoretically using concepts from computational learning theory, and at the same time can achieve good performance when applied to real problems. Examples of these real-world applications are provided by Sue Dumais, who describes the aforementioned text-categorization problem, yielding the best results to date on the Reuters collection, and Edgar Osuna, who presents strong results on application to face detection. Our fourth author, John Platt, gives us a practical guide and a new technique for implementing the algorithm efficiently.}, author = {Hearst, Marti A.}, citeulike-article-id = {820314}, journal = {IEEE Intelligent Systems}, keywords = {svm}, posted-at = {2006-08-29 02:48:21}, priority = {4}, title = {Support vector machines} }

TY - JOUR ID - citeulike:820314 L3 - citeulike-article-id:820314 N2 - My first exposure to Support Vector Machines came this spring when I heard Sue Dumais present impressive results on text categorization using this analysis technique. This issue’s collection of essays should help familiarize our readers with this interesting new racehorse in the Machine Learning stable. Bernhard Schölkopf, in an introductory overview, points out that a particular advantage of SVMs over other learning algorithms is that it can be analyzed theoretically using concepts from computational learning theory, and at the same time can achieve good performance when applied to real problems. Examples of these real-world applications are provided by Sue Dumais, who describes the aforementioned text-categorization problem, yielding the best results to date on the Reuters collection, and Edgar Osuna, who presents strong results on application to face detection. Our fourth author, John Platt, gives us a practical guide and a new technique for implementing the algorithm efficiently. JF - IEEE Intelligent Systems TI - Support vector machines KW - svm AU - Hearst, Marti ER -