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Chapman & Hall/CRC Computer Science & Data Analysis #17: Exploratory Data Analysis with MATLAB, Second Edition

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Chapman & Hall/CRC Computer Science & Data Analysis #17: Exploratory Data Analysis with MATLAB, Second Edition Cover

 

Synopses & Reviews

Publisher Comments:

Since the publication of the bestselling first edition, many advances have been made in exploratory data analysis (EDA). Covering innovative approaches for dimensionality reduction, clustering, and visualization, Exploratory Data Analysis with MATLAB, Second Edition uses numerous examples and applications to show how the methods are used in practice.

New to the Second Edition

  • Discussions of nonnegative matrix factorization, linear discriminant analysis, curvilinear component analysis, independent component analysis, and smoothing splines
  • An expanded set of methods for estimating the intrinsic dimensionality of a data set
  • Several clustering methods, including probabilistic latent semantic analysis and spectral-based clustering
  • Additional visualization methods, such as a rangefinder boxplot, scatterplots with marginal histograms, biplots, and a new method called Andrews images
  • Instructions on a free MATLAB GUI toolbox for EDA

Like its predecessor, this edition continues to focus on using EDA methods, rather than theoretical aspects. The MATLAB codes for the examples, EDA toolboxes, data sets, and color versions of all figures are available for download at http: //pi-sigma.info

Book News Annotation:

The second edition of this textbook on exploratory data analysis (EDA) provides updated information in a variety of areas including linear dimensionality reduction, independent component analysis and improved visualization methods including boxplots, scatterplots and histograms. In keeping with the philosophy of the first edition this volume continues to provide practical rather than theoretical instruction on performing EDA procedures with the MATLAB technical computing software. The work includes numerous illustrations and graphs as well as code examples and online access to additional resources including MATLAB code, sample data sets and color graphs is provided. Angel Martinez is a statistics professor at Strayer University, Wendy Martinez has worked for the US Navy Office of Naval Research and Solka works for the Naval Surface Warfare Center. Annotation ©2011 Book News, Inc., Portland, OR (booknews.com)

Synopsis:

"Using MATLAB to illustrate computational aspects of EDA, this second edition updates all the techniques and improves the Toolboxes in each chapter. The authors extensively use MATLAB code and algorithm descriptions to provide state-of-the-art techniques for finding patterns and structure in data. Addressing theory, they also incorporate many annotated references to direct readers to the more theoretical aspects of the methods. The book presents an approach using only the basic functions from MATLAB and the MATLAB Statistics Toolbox in order to be more accessible and enduring. It also contains pseudo-code to enable users of other software packages to implement the algorithms"--

Product Details

ISBN:
9781439812204
Author:
Martinez, Wendy L.
Publisher:
CRC Press
Author:
Martinez, Angel
Author:
Solka, Jeffrey
Subject:
Statistics
Subject:
Probability & Statistics - General
Subject:
Mathematics - Statistics
Edition Description:
New
Series:
Chapman & Hall/CRC Computer Science & Data Analysis
Series Volume:
17
Publication Date:
20101231
Binding:
Hardcover
Language:
English
Pages:
512

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Chapman & Hall/CRC Computer Science & Data Analysis #17: Exploratory Data Analysis with MATLAB, Second Edition New Hardcover
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Product details 512 pages CRC Press - English 9781439812204 Reviews:
"Synopsis" by , "Using MATLAB to illustrate computational aspects of EDA, this second edition updates all the techniques and improves the Toolboxes in each chapter. The authors extensively use MATLAB code and algorithm descriptions to provide state-of-the-art techniques for finding patterns and structure in data. Addressing theory, they also incorporate many annotated references to direct readers to the more theoretical aspects of the methods. The book presents an approach using only the basic functions from MATLAB and the MATLAB Statistics Toolbox in order to be more accessible and enduring. It also contains pseudo-code to enable users of other software packages to implement the algorithms"--
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