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|a (OCoLC)1048922046
|z (OCoLC)993991827
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|b Ingram Content Group
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|a QA278
|b .M3735 2017eb
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|a HCDD
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1 |
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|a Martinez, Wendy L.,
|e author.
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1 |
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|a Exploratory data analysis with MATLAB /
|c Wendy L. Martinez, Angel R. Matinez, Jeffrey L. Solka.
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| 250 |
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|a Third edition.
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| 264 |
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1 |
|a Boca Raton, FL :
|b CRC Press, Taylor & Francis Group,
|c [2017]
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| 300 |
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|a 1 online resource (625 pages)
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| 336 |
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|a text
|b txt
|2 rdacontent
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| 337 |
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|a computer
|b c
|2 rdamedia
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| 338 |
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|a online resource
|b cr
|2 rdacarrier
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| 490 |
1 |
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|a Chapman & Hall/CRC computer science and data analysis series
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0 |
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|a Print version record.
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|a Intro; Half Title; Series Editor; Title; Copyrights; Dedication; Table of Contents; Preface to the Third Edition; Preface to the Second Edition; Preface to the First Edition; Part I Introduction to Exploratory Data Analysis; Chapter 1 Introduction to Exploratory Data Analysis; 1.1 What is Exploratory Data Analysis; 1.2 Overview of the Text; 1.3 A Few Words about Notation; 1.4 Data Sets Used in the Book; 1.4.1 Unstructured Text Documents; 1.4.2 Gene Expression Data; 1.4.3 Oronsay Data Set; 1.4.4 Software Inspection; 1.5 Transforming Data; 1.5.1 Power Transformations; 1.5.2 Standardization.
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|a 1.5.3 Sphering the Data1.6 Further Reading; Exercises; Part II EDA as Pattern Discovery; Chapter 2 Dimensionality Reduction -- Linear Methods; 2.1 Introduction; 2.2 Principal Component Analysis -- PCA; 2.2.1 PCA Using the Sample Covariance Matrix; 2.2.2 PCA Using the Sample Correlation Matrix; 2.2.3 How Many Dimensions Should We Keep; 2.3 Singular Value Decomposition -- SVD; 2.4 Nonnegative Matrix Factorization; 2.5 Factor Analysis; 2.6 Fisher's Linear Discriminant; 2.7 Random Projections; 2.8 Intrinsic Dimensionality; 2.8.1 Nearest Neighbor Approach; 2.8.2 Correlation Dimension.
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|a 2.8.3 Maximum Likelihood Approach2.8.4 Estimation Using Packing Numbers; 2.8.5 Estimation of Local Dimension; 2.9 Summary and Further Reading; Exercises; Chapter 3 Dimensionality Reduction-Nonlinear Methods; 3.1 Multidimensional Scaling -- MDS; 3.1.1 Metric MDS; 3.1.2 Nonmetric MDS; 3.2 Manifold Learning; 3.2.1 Locally Linear Embedding; 3.2.2 Isometric Feature Mapping -- ISOMAP; 3.2.3 Hessian Eigenmaps; 3.3 Artificial Neural Network Approaches; 3.3.1 Self-Organizing Maps; 3.3.2 Generative Topographic Maps; 3.3.3 Curvilinear Component Analysis; 3.3.4 Autoencoders.
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|a 3.4 Stochastic Neighbor Embedding3.5 Summary and Further Reading; Exercises; Chapter 4 Data Tours; 4.1 Grand Tour; 4.1.1 Torus Winding Method; 4.1.2 Pseudo Grand Tour; 4.2 Interpolation Tours; 4.3 Projection Pursuit; 4.4 Projection Pursuit Indexes; 4.4.1 Posse Chi-Square Index; 4.4.2 Moment Index; 4.5 Independent Component Analysis; 4.6 Summary and Further Reading; Exercises; Chapter 5 Finding Clusters; 5.1 Introduction; 5.2 Hierarchical Methods; 5.3 Optimization Methods- k-Means; 5.4 Spectral Clustering; 5.5 Document Clustering; 5.5.1 Nonnegative Matrix Factorization -- Revisited.
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|a 5.5.2 Probabilistic Latent Semantic Analysis5.6 Minimum Spanning Trees and Clustering; 5.6.1 Definitions; 5.6.2 Minimum Spanning Tree Clustering; 5.7 Evaluating the Clusters; 5.7.1 Rand Index; 5.7.2 Cophenetic Correlation; 5.7.3 Upper Tail Rule; 5.7.4 Silhouette Plot; 5.7.5 Gap Statistic; 5.7.6 Cluster Validity Indices; 5.8 Summary and Further Reading; Exercises; Chapter 6 Model-Based Clustering; 6.1 Overview of Model-Based Clustering; 6.2 Finite Mixtures; 6.2.1 Multivariate Finite Mixtures; 6.2.2 Component Models -- Constraining the Covariances; 6.3 Expectation-Maximization Algorithm.
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| 500 |
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|a 6.4 Hierarchical Agglomerative Model-Based Clustering.
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| 520 |
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|a Exploratory Data Analysis with MATLAB, Third Edition presents EDA methods from a computational perspective and uses numerous examples and applications to show how the methods are used in practice. The authors use MATLAB code, pseudo-code, and algorithm descriptions to illustrate the concepts. The MATLAB code for examples, data sets, and the EDA Toolbox are available for download on the book's website. --
|c Provided by publisher.
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| 504 |
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|a Includes bibliographical references and indexes.
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| 630 |
0 |
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|a MATLAB.
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| 630 |
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7 |
|a MATLAB
|2 fast
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| 650 |
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|a Multivariate analysis.
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| 650 |
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|a Mathematical statistics.
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| 650 |
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|a Mathematical statistics
|2 fast
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| 650 |
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7 |
|a Multivariate analysis
|2 fast
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| 700 |
1 |
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|a Martinez, Angel R.,
|e author.
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| 700 |
1 |
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|a Solka, Jeffrey,
|e author.
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| 776 |
0 |
8 |
|i Print version:
|a Martinez, Wendy L.
|t Exploratory data analysis with MATLAB.
|d Boca Raton : Chapman and Hall/CRC, [2017]
|z 9781498776066
|w (OCoLC)959965302
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| 830 |
|
0 |
|a Series in computer science and data analysis.
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| 856 |
4 |
0 |
|u https://ebookcentral.proquest.com/lib/holycrosscollege-ebooks/detail.action?docID=5475665
|y Click for online access
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|a EBC-AC
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|a 92
|b HCD
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