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About this product
- Author(s)Angel R. Martinez,Jeffrey Solka,Wendy L. Martinez
- PublisherTaylor & Francis Inc
- Date of Publication17/12/2010
- GenreSoftware Packages
- Place of PublicationBosa Roca
- Country of PublicationUnited States
- ImprintCRC Press Inc
- Content Note133 black & white illustrations, 15 colour illustrations, 11 black & white tables
- Weight907 g
- Width156 mm
- Height234 mm
- Spine30 mm
- Format DetailsUnsewn / adhesive bound
- Edition Statement2nd Revised edition
- Table Of ContentsINTRODUCTION TO EXPLORATORY DATA ANALYSIS Introduction to Exploratory Data Analysis What Is Exploratory Data Analysis Overview of the Text A Few Words about Notation Data Sets Used in the Book Transforming Data EDA AS PATTERN DISCOVERY Dimensionality Reduction - Linear Methods Introduction Principal Component Analysis (PCA) Singular Value Decomposition (SVD) Nonnegative Matrix Factorization Factor Analysis Fisher's Linear Discriminant Intrinsic Dimensionality Dimensionality Reduction - Nonlinear Methods Multidimensional Scaling (MDS) Manifold Learning Artificial Neural Network Approaches Data Tours Grand Tour Interpolation Tours Projection Pursuit Projection Pursuit Indexes Independent Component Analysis Finding Clusters Introduction Hierarchical Methods Optimization Methods-k-Means Spectral Clustering Document Clustering Evaluating the Clusters Model-Based Clustering Overview of Model-Based Clustering Finite Mixtures Expectation-Maximization Algorithm Hierarchical Agglomerative Model-Based Clustering Model-Based Clustering MBC for Density Estimation and Discriminant Analysis Generating Random Variables from a Mixture Model Smoothing Scatterplots Introduction Loess Robust Loess Residuals and Diagnostics with Loess Smoothing Splines Choosing the Smoothing Parameter Bivariate Distribution Smooths Curve Fitting Toolbox GRAPHICAL METHODS FOR EDA Visualizing Clusters Dendrogram Treemaps Rectangle Plots ReClus Plots Data Image Distribution Shapes Histograms Boxplots Quantile Plots Bagplots Rangefinder Boxplot Multivariate Visualization Glyph Plots Scatterplots Dynamic Graphics Coplots Dot Charts Plotting Points as Curves Data Tours Revisited Biplots 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 References Index Summary, Further Reading, and Exercises appear at the end of each chapter.
- Author BiographyWendy L. Martinez has been in government service for over 20 years, working with leading researchers from academia, industry, and government labs. During this time, she has conducted and published research in text data mining, probability density estimation, signal processing, scientific visualization, and statistical pattern recognition. A fellow of the American Statistical Association, she earned an M.S. in aerospace engineering from George Washington University and a Ph.D. in computational sciences and informatics from George Mason University. Angel R. Martinez teaches undergraduate and graduate courses in statistics and mathematics at Strayer University. Before retiring from government service, he worked for the U.S. Navy as an operations research analyst and a computer scientist. He earned an M.S. in systems engineering from the Virginia Polytechnic Institute and State University and a Ph.D. in computational sciences and informatics from George Mason University. Since 1984, Jeffrey L. Solka has been working in statistical pattern recognition for the Department of the Navy. He has published over 120 journal, conference, and technical papers; has won numerous awards; and holds 4 patents. He earned an M.S. in mathematics from James Madison University, an M.S. in physics from Virginia Polytechnic Institute and State University, and a Ph.D. in computational sciences and informatics from George Mason University.
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