Exploratory Data Analysis With Matlab
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Exploratory Data Analysis With Matlab
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Author : Wendy L. Martinez
language : en
Publisher: CRC Press
Release Date : 2004-11-29
Exploratory Data Analysis With Matlab written by Wendy L. Martinez and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2004-11-29 with Business & Economics categories.
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.
Exploratory Data Analysis With Matlab
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Author : Wendy L. Martinez
language : en
Publisher: CRC Press
Release Date : 2017-08-07
Exploratory Data Analysis With Matlab written by Wendy L. Martinez and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-08-07 with Mathematics categories.
Praise for the Second Edition: "The authors present an intuitive and easy-to-read book. ... accompanied by many examples, proposed exercises, good references, and comprehensive appendices that initiate the reader unfamiliar with MATLAB."—Adolfo Alvarez Pinto, International Statistical Review "Practitioners of EDA who use MATLAB will want a copy of this book. ... The authors have done a great service by bringing together so many EDA routines, but their main accomplishment in this dynamic text is providing the understanding and tools to do EDA. —David A Huckaby, MAA Reviews Exploratory Data Analysis (EDA) is an important part of the data analysis process. The methods presented in this text are ones that should be in the toolkit of every data scientist. As computational sophistication has increased and data sets have grown in size and complexity, EDA has become an even more important process for visualizing and summarizing data before making assumptions to generate hypotheses and models. 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. New to the Third Edition Random projections and estimating local intrinsic dimensionality Deep learning autoencoders and stochastic neighbor embedding Minimum spanning tree and additional cluster validity indices Kernel density estimation Plots for visualizing data distributions, such as beanplots and violin plots A chapter on visualizing categorical data
Exploratory Data Analysis With Matlab Second Edition
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Author : Wendy L. Martinez
language : en
Publisher: CRC Press
Release Date : 2010-12-16
Exploratory Data Analysis With Matlab Second Edition written by Wendy L. Martinez and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2010-12-16 with Business & Economics categories.
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
Combinatorial Inference In Geometric Data Analysis
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Author : Brigitte Le Roux
language : en
Publisher: CRC Press
Release Date : 2019-03-20
Combinatorial Inference In Geometric Data Analysis written by Brigitte Le Roux and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-03-20 with Mathematics categories.
Geometric Data Analysis designates the approach of Multivariate Statistics that conceptualizes the set of observations as a Euclidean cloud of points. Combinatorial Inference in Geometric Data Analysis gives an overview of multidimensional statistical inference methods applicable to clouds of points that make no assumption on the process of generating data or distributions, and that are not based on random modelling but on permutation procedures recasting in a combinatorial framework. It focuses particularly on the comparison of a group of observations to a reference population (combinatorial test) or to a reference value of a location parameter (geometric test), and on problems of homogeneity, that is the comparison of several groups for two basic designs. These methods involve the use of combinatorial procedures to build a reference set in which we place the data. The chosen test statistics lead to original extensions, such as the geometric interpretation of the observed level, and the construction of a compatibility region. Features: Defines precisely the object under study in the context of multidimensional procedures, that is clouds of points Presents combinatorial tests and related computations with R and Coheris SPAD software Includes four original case studies to illustrate application of the tests Includes necessary mathematical background to ensure it is self–contained This book is suitable for researchers and students of multivariate statistics, as well as applied researchers of various scientific disciplines. It could be used for a specialized course taught at either master or PhD level.
Fundamentals Of Data Science
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Author : Sanjeev J. Wagh
language : en
Publisher: CRC Press
Release Date : 2021-09-26
Fundamentals Of Data Science written by Sanjeev J. Wagh and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-09-26 with Business & Economics categories.
Fundamentals of Data Science is designed for students, academicians and practitioners with a complete walkthrough right from the foundational groundwork required to outlining all the concepts, techniques and tools required to understand Data Science. Data Science is an umbrella term for the non-traditional techniques and technologies that are required to collect, aggregate, process, and gain insights from massive datasets. This book offers all the processes, methodologies, various steps like data acquisition, pre-process, mining, prediction, and visualization tools for extracting insights from vast amounts of data by the use of various scientific methods, algorithms, and processes Readers will learn the steps necessary to create the application with SQl, NoSQL, Python, R, Matlab, Octave and Tablue. This book provides a stepwise approach to building solutions to data science applications right from understanding the fundamentals, performing data analytics to writing source code. All the concepts are discussed in simple English to help the community to become Data Scientist without much pre-requisite knowledge. Features : Simple strategies for developing statistical models that analyze data and detect patterns, trends, and relationships in data sets. Complete roadmap to Data Science approach with dedicatedsections which includes Fundamentals, Methodology and Tools. Focussed approach for learning and practice various Data Science Toolswith Sample code and examples for practice. Information is presented in an accessible way for students, researchers and academicians and professionals.
Data Science Foundations
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Author : Fionn Murtagh
language : en
Publisher: CRC Press
Release Date : 2017-09-22
Data Science Foundations written by Fionn Murtagh and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-09-22 with Computers categories.
"Data Science Foundations is most welcome and, indeed, a piece of literature that the field is very much in need of...quite different from most data analytics texts which largely ignore foundational concepts and simply present a cookbook of methods...a very useful text and I would certainly use it in my teaching." - Mark Girolami, Warwick University Data Science encompasses the traditional disciplines of mathematics, statistics, data analysis, machine learning, and pattern recognition. This book is designed to provide a new framework for Data Science, based on a solid foundation in mathematics and computational science. It is written in an accessible style, for readers who are engaged with the subject but not necessarily experts in all aspects. It includes a wide range of case studies from diverse fields, and seeks to inspire and motivate the reader with respect to data, associated information, and derived knowledge.
Time Series Clustering And Classification
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Author : Elizabeth Ann Maharaj
language : en
Publisher: CRC Press
Release Date : 2019-03-19
Time Series Clustering And Classification written by Elizabeth Ann Maharaj and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-03-19 with Mathematics categories.
The beginning of the age of artificial intelligence and machine learning has created new challenges and opportunities for data analysts, statisticians, mathematicians, econometricians, computer scientists and many others. At the root of these techniques are algorithms and methods for clustering and classifying different types of large datasets, including time series data. Time Series Clustering and Classification includes relevant developments on observation-based, feature-based and model-based traditional and fuzzy clustering methods, feature-based and model-based classification methods, and machine learning methods. It presents a broad and self-contained overview of techniques for both researchers and students. Features Provides an overview of the methods and applications of pattern recognition of time series Covers a wide range of techniques, including unsupervised and supervised approaches Includes a range of real examples from medicine, finance, environmental science, and more R and MATLAB code, and relevant data sets are available on a supplementary website
Matlab Roadmap To Applications
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Author : Yi Chen
language : en
Publisher: Springer Nature
Release Date : 2025-03-28
Matlab Roadmap To Applications written by Yi Chen and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-03-28 with Computers categories.
This open access book presents a comprehensive guide to MATLAB programming, catering to students, engineers, and researchers seeking to harness MATLAB as a powerful tool for their work. The text meticulously covers fundamental concepts, progressing from basic elements such as types and operators to more complex structures like arrays and matrices. It elucidates key programming constructs including selection statements, loop structures, scripts, and functions, providing readers with a solid foundation in MATLAB programming. The book's structure is carefully crafted to facilitate step-by-step learning, with each chapter building upon previous knowledge. Abundant examples and exercises reinforce understanding, while dedicated sections on data visualisation, algorithm development, and practical applications in engineering, science, and finance demonstrate MATLAB's versatility across disciplines. A distinguishing feature of this volume is its inclusion of laboratory work and coursework, allowing readers to apply theoretical concepts to real-world scenarios. This hands-on approach enhances the learning experience and prepares users for practical implementation of MATLAB in their respective fields. In the current era of artificial intelligence, this book serves as an essential resource for those seeking to leverage MATLAB's capabilities. It not only equips readers with programming skills but also illustrates how MATLAB can be integrated into cutting-edge research and industry applications.
Journal Of The American Statistical Association
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Author :
language : en
Publisher:
Release Date : 2008
Journal Of The American Statistical Association written by and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2008 with Electronic journals categories.
Textual Data Science With R
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Author : Mónica Bécue-Bertaut
language : en
Publisher: CRC Press
Release Date : 2019-03-11
Textual Data Science With R written by Mónica Bécue-Bertaut and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-03-11 with Mathematics categories.
Textual Statistics with R comprehensively covers the main multidimensional methods in textual statistics supported by a specially-written package in R. Methods discussed include correspondence analysis, clustering, and multiple factor analysis for contigency tables. Each method is illuminated by applications. The book is aimed at researchers and students in statistics, social sciences, hiistory, literature and linguistics. The book will be of interest to anyone from practitioners needing to extract information from texts to students in the field of massive data, where the ability to process textual data is becoming essential.