This comprehensive volume presents the foundations of linear algebra ideas and techniques applied to data mining and related fields. Linear algebra has gained increasing importance in data mining and pattern recognition, as shown by the many current data mining publications, and has a strong impact in other disciplines like psychology, chemistry, and biology. The basic material is accompanied by more than 550 exercises and supplements, many accompanied with complete solutions and MATLAB applications.
Sprache
Verlagsort
Zielgruppe
Für höhere Schule und Studium
Für Beruf und Forschung
Professionals, academics, and graduate students in pattern recognition and artificial intelligence
Produkt-Hinweis
Fadenheftung
Gewebe-Einband
Maße
Höhe: 235 mm
Breite: 157 mm
Dicke: 51 mm
Gewicht
ISBN-13
978-981-4383-49-3 (9789814383493)
Copyright in bibliographic data and cover images is held by Nielsen Book Services Limited or by the publishers or by their respective licensors: all rights reserved.
Schweitzer Klassifikation
Autor*in
Univ Of Massachusetts Boston, Usa
Modules and Linear Spaces; Matrices; MATLAV; Determinants; Norms on Linear Spaces; Inner Product Spaces; Convexity; Eigenvalues; Similarity and Spectra; Singular Values; Graphs and Matrices; Data Sample Matrices; Least Squares Approximation and Data Mining; Dimensionality Reduction Techniques; The K-Means Clustering Algorithm; Spectral Properties of Graphs and Spectral Clustering.
