Linear Algebra Tools For Data Mining
Published on 1. February 2012
Book
Hardback
880 pages
978-981-4383-49-3 (ISBN)
Description
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.
More details
Language
English
Place of publication
Singapore
Singapore
Target group
College/higher education
Professional and scholarly
Professionals, academics, and graduate students in pattern recognition and artificial intelligence
Dimensions
Height: 235 mm
Width: 157 mm
Thickness: 51 mm
Weight
1400 gr
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 Classification
Person
Content
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.