Exploratory Data Analysis with MATLAB

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ISBN 9781584883661
Cat# C3669
 

Features

  • Provides MATLAB code for virtually all algorithms covered in the text
  • Includes pseudo-code to implement algorithms in software other than MATLAB
  • Uses robust code to make the material accessible to more users and to prolong the book's usable life
  • Offers many MATLAB GUIs for linking, brushing, model based clustering, grand tour, parallel coordinates, and much more available in the downloadable EDA Toolbox
  • Contains an eight-page, full-color insert illustrating data output from several MATLAB examples
  • Summary

    Exploratory data analysis (EDA) was conceived at a time when computers were not widely used, and thus computational ability was rather limited. As computational sophistication has increased, EDA has become an even more powerful process for visualizing and summarizing data before making model assumptions to generate hypotheses, encompassing larger and more complex data sets. There are many resources for those interested in the theory of EDA, but this is the first book to use MATLAB to illustrate the computational aspects of this discipline.

    Exploratory Data Analysis with MATLAB presents the methods of EDA from a computational perspective. 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 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.

    This text places the tools needed to implement EDA theory at the fingertips of researchers, applied mathematicians, computer scientists, engineers, and statisticians by using a practical/computational approach.

    Table of Contents

    INTRODUCTION TO EXPLORATORY DATA ANALYSIS
    Introduction to Exploratory Data Analysis
    EDA AS PATTERN DISCOVERY
    Dimensionality Reduction - Linear Methods
    Dimensionality Reduction - Nonlinear Methods
    Data Tours
    Finding Clusters
    Model-Based Clustering
    Smoothing Scatterplots
    GRAPHICAL METHODS FOR EDA
    Visualizing Clusters
    Distribution Shapes
    Multivariate Visualization
    APPENDIX A: PROXIMITY MEASURES
    APPENDIX B: SOFTWARE RESOURCES FOR EDA
    APPENDIX C: DESCRIPTION OF DATA SETS
    APPENDIX D: INTRODUCTION TO MATLAB
    APPENDIX E: MATLAB FUNCTIONS

    Editorial Reviews

    "This book … has a good introduction to EDA, and then illustrates several applications where MATLAB provides the analysis of data to produce unexpected results."
    - Books-on-Line

    "This is a book for those who have a good grounding in linear algebra and statistics who wish to use MATLAB for statistical investigations."
    -Short Book Reviews of the International Statistical Institute

    "The aim of this book, as stated by the authors, is to 'make exploratory data analysis (EDA) techniques available to a wide range of users.' They have succeeded to a commendable extent in achieving this goal. The audience for the book is a wide one and includes statisticians, computer scientists, and others who may be interested in or use EDA. …I found the book to be engagingly written, and successful in its defined task of teaching the reader to use EDA with MATLAB. I liked the graphics and thought that they fully illustrated the techniques used."
    -Journal of the American Statistical Association, Brian Jersky, Sonoma State University

    "The book can also be useful in a classroom setting at the senior undergraduate and graduate level, valuable exercises being included in each chapter."
    -Zentralblatt MATH, Neculai Curteanu

    Downloads Updates


    Resource OS Platform Updated Description Instructions
    C3669_1.zip Cross Platform December 15, 2004
    C3669_2.zip Cross Platform December 16, 2004
    EDAGUIToolboxV1.zip Cross Platform December 18, 2006
    EDAGUIv1p1.zip Cross Platform March 06, 2007

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