Matrix Methods in Data Mining and Pattern Recognition Eldén Paperback

Matrix Methods in Data Mining and Pattern RecognitionAuthor(s): Lars Eld?n\nFormat: Paperback\nPublisher: Society for Industrial & Applied Mathematics,U.S., United States\nImprint: Society for Industrial & Applied Mathematics,U.S.\nISBN-13: 9781611975857, 978-1611975857\nSynopsis\nThis thoroughly revised second edition provides an updated treatment of numerical linear algebra techniques for solving problems in data mining and pattern recognition. Adopting an application-oriented approach, the author introduces matrix theory and decompositions, describes how modern matrix methods can be applied in real life scenarios, and provides a set of tools that students can modify for a particular application.\n\nBuilding on material from the first edition, the author discusses basic graph concepts and their matrix counterparts. He introduces the graph Laplacian and properties of its eigenvectors needed in spectral partitioning and describes spectral graph partitioning applied to social .