Exploratory Data Analysis with MATLAB


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1 Computer Science and Data Analysis Series Exploratory Data Analysis with MATLAB Second Edition Wendy L Martinez Angel R. Martinez Jeffrey L. Solka ( r ec) CRC Press VV J Taylor & Francis Group Boca Raton London New York CRC Press is an imprint of the Taylor & Francis Group, an informa business A CHAPMAN & HALL BOOK
2 Table of Contents Preface to the Second Edition Preface to the First Edition xiii xvii Parti Introduction to Exploratory Data Analysis Chapter 1 Introduction to Exploratory Data Analysis 1.1 What is Exploratory Data Analysis Overview of the Text A Few Words about Notation Data Sets Used in the Book Unstructured Text Documents Gene Expression Data Oronsay Data Set Software Inspection Transforming Data Power Transformations Standardization Sphering the Data Further Reading 25 Exercises 27 Part II EDA as Pattern Discovery Chapter 2 Dimensionality Reduction Linear Methods 2.1 Introduction Principal Component Analysis PCA PCA Using the Sample Covariance Matrix PCA Using the Sample Correlation Matrix How Many Dimensions Should We Keep? Singular Value Decomposition SVD Nonnegative Matrix Factorization 47 vii
3 Vlll Exploratory Data Analysis with MATLAB, 2 nd Edition 2.5 Factor Analysis Fisher's Linear Discriminant Intrinsic Dimensionality Nearest Neighbor Approach Correlation Dimension Maximum Likelihood Approach Estimation Using Packing Numbers Summary and Further Reading 72 Exercises 73 Chapter 3 Dimensionality Reduction Nonlinear Methods 3.1 Multidimensional Scaling MDS Metric MDS Nonmetric MDS Manifold Learning Locally Linear Embedding Isometric Feature Mapping ISOMAP Hessian Eigenmaps Artificial Neural Network Approaches SelfOrganizing Maps Generative Topographic Maps Ill Curvilinear Component Analysis Summary and Further Reading 121 Exercises 122 Chapter 4 Data Tours 4.1 Grand Tour Torus Winding Method Pseudo Grand Tour Interpolation Tours Projection Pursuit Projection Pursuit Indexes Posse ChiSquare Index Moment Index Independent Component Analysis Summary and Further Reading 151 Exercises 152 Chapter 5 Finding Clusters 5.1 Introduction Hierarchical Methods 157
4 Table of Contents ix 5.3 Optimization Methods fcmeans Spectral Clustering Document Clustering Nonnegative Matrix Factorization Revisited Probabilistic Latent Semantic Analysis Evaluating the Clusters Rand Index Cophenetic Correlation Upper Tail Rule Silhouette Plot Gap Statistic Summary and Further Reading 197 Exercises 200 Chapter 6 ModelBased Clustering 6.1 Overview of ModelBased Clustering Finite Mixtures Multivariate Finite Mixtures Component Models Constraining the Covariances ExpectationMaximization Algorithm Hierarchical Agglomerative ModelBased Clustering ModelBased Clustering MBC for Density Estimation and Discriminant Analysis Introduction to Pattern Recognition Bayes Decision Theory Estimating Probability Densities with MBC Generating Random Variables from a Mixture Model Summary and Further Reading 241 Exercises 244 Chapter 7 Smoothing Scatterplots 7.1 Introduction Loess Robust Loess Residuals and Diagnostics with Loess Residual Plots Spread Smooth Loess Envelopes Upper and Lower Smooths Smoothing Splines Regression with Splines Smoothing Splines Smoothing Splines for Uniformly Spaced Data Choosing the Smoothing Parameter 281
5 x Exploratory Data Analysis with MATLAB, 2 nd Edition 7.7 Bivariate Distribution Smooths Pairs of Middle Smoothings Polar Smoothing Curve Fitting Toolbox Summary and Further Reading 293 Exercises 294 Part III Graphical Methods for EDA Chapter 8 Visualizing Clusters 8.1 Dendrogram Treemaps Rectangle Plots ReClus Plots Data Image Summary and Further Reading 323 Exercises 324 Chapter 9 Distribution Shapes 9.1 Histograms Univariate Histograms Bivariate Histograms Boxplots The Basic Boxplot Variations of the Basic Boxplot Quantile Plots Probability Plots QuantileQuantile Plot Quantile Plot Bagplots Rangefinder Boxplot Summary and Further Reading 359 Exercises 361 Chapter 10 Multivariate Visualization 10.1 Glyph Plots Scatterplots D and 3D Scatterplots Scatterplot Matrices Scatterplots with Hexagonal Binning 372
6 Table of Contents xi 10.3 Dynamic Graphics Identification of Data Linking Brushing Coplots Dot Charts Basic Dot Chart Multiway Dot Chart Plotting Points as Curves Parallel Coordinate Plots Andrews' Curves Andrews' Images More Plot Matrices Data Tours Revisited Grand Tour Permutation Tour Biplots Summary and Further Reading 411 Exercises 413 Appendix A Proximity Measures A.l Definitions 417 A.1.1 Dissimilarities 418 A.1.2 Similarity Measures 420 A.1.3 Similarity Measures for Binary Data 420 A.l.4 Dissimilarities for Probability Density Functions 421 A.2 Transformations 422 A.3 Further Reading 423 Appendix В Software Resources for EDA B.l MATLAB Programs 425 B.2 Other Programs for EDA 429 B.3 EDA Toolbox 431 Appendix С Description of Data Sets 433 Appendix D Introduction to MATLAB D.l What Is MATLAB? 439 D.2 Getting Help in MATLAB 440 D.3 File and Workspace Management 440
7 XII Exploratory Data Analysis with MATLAB, 2 nd Edition D.4 Punctuation in MATLAB 443 D.5 Arithmetic Operators 444 D.6 Data Constructs in MATLAB 444 Basic Data Constructs 444 Building Arrays 445 Cell Arrays 445 Structures 447 D.7 Script Files and Functions 447 D.8 Control Flow 448 for Loop 448 while Loop 449 ifelse Statements 449 switch Statement 449 D.9 Simple Plotting 450 D.10 Where to get MATLAB Information 452 Appendix E MATLAB Functions E.l MATLAB 455 E.2 Statistics Toolbox 457 E.3 Exploratory Data Analysis Toolbox 458 E.4 EDA GUI Toolbox 459 References 475 Author Index 497 Subject Index 503
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