
06002676
b
2012e.00641
Simovici, Dan A.
Linear algebra tools for data mining.
Hackensack, NJ: World Scientific (ISBN 9789814383493/hbk; 9789814383509/ebook). xiv, 863~p. (2012).
2012
Hackensack, NJ: World Scientific
EN
H15
H65
linear algebra
matrix theory
numerical linear algebra
computer science
learning theory
textbook
data mining
pattern recognition
modules
interactive system
MATLAB
determinants
norms
inner product
eigenvalues
similarity
spectra
singular values
graphs
sample matrices
biplots
least squares approximation
principle component analysis
$k$means algorithm
convexity
spectral clustering
doi:10.1142/8360
The book is divided in two parts and is intended to graduate students and researchers who have concerns in data mining and pattern recognition. In order to help the readers interested in applications presented in this volume, the author includes in the first part the most of the mathematical background that is needed: modules and linear spaces, matrices, interactive system  MATLAB, determinants, norms, inner product, convexity, eigenvalues, similarity and spectra, singular values. In the second part ``Applications'' included are: graphs, sample matrices, biplots, least squares approximation, principal component analysis, the $k$means algorithm and convexity, spectral clustering algorithms, etc.
Costic\u{a} Moro\c sanu (Ia\c si)