Matrix methods in data mining and pattern recognition / Lars Eldén
Tipo de material:
TextoSeries Fundamentals of algorithmsEditor: Philadelphia, PA : Society for Industrial and Applied Mathematics, 2007Descripción: x, 224 páginas : ilustracionesTipo de contenido: texto Tipo de medio: no mediado Tipo de portador: volumenISBN: 9780898716269 ; 0898716268 Tema(s): MINERIA DE DATOS | SISTEMA DE RECONOCIMIENTO DE MODELOS ( Computadores) -- MODELOS MATEMATICOS | ÁLGEBRA LINEALClasificación CDD: 005.74 Recursos en línea: Ver registro electrónico
Contenidos:
Preface; Part I. Linear Algebra Concepts and Matrix Decompositions: 1. Vectors and matrices in data mining and pattern recognition; 2. Vectors and matrices; 3. Linear systems and least squares; 4. Orthogonality; 5. QR decomposition; 6. Singular value decomposition; 7. Reduced rank least squares models; 8. Tensor decomposition; 9. Clustering and non-negative matrix factorization; Part II. Data Mining Applications: 10. Classification of handwritten digits; 11. Text mining; 12. Page ranking for a Web search engine; 13. Automatic key word and key sentence extraction; 14. Face recognition using rensor SVD; Part III. Computing the Matrix Decompositions: 15. Computing Eigenvalues and singular values; Bibliography; Index.
| Tipo de ítem | Biblioteca actual | Colección | número de clasificación | Copia número | Estado | Fecha de vencimiento | Código de barras |
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Libro General
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Biblioteca Central | Colección General | 005.74 E37 (Navegar estantería(Abre debajo)) | 1 | Disponible | 3560900273495 |
Preface; Part I. Linear Algebra Concepts and Matrix Decompositions: 1. Vectors and matrices in data mining and pattern recognition; 2. Vectors and matrices; 3. Linear systems and least squares; 4. Orthogonality; 5. QR decomposition; 6. Singular value decomposition; 7. Reduced rank least squares models; 8. Tensor decomposition; 9. Clustering and non-negative matrix factorization; Part II. Data Mining Applications: 10. Classification of handwritten digits; 11. Text mining; 12. Page ranking for a Web search engine; 13. Automatic key word and key sentence extraction; 14. Face recognition using rensor SVD; Part III. Computing the Matrix Decompositions: 15. Computing Eigenvalues and singular values; Bibliography; Index.