Text Mining With Matlab 2nd Edition
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Text Mining With Matlab 2nd Edition
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Author : Rafael E. Banchs
language : en
Publisher:
Release Date : 2021
Text Mining With Matlab 2nd Edition written by Rafael E. Banchs and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021 with Data mining categories.
This book provides a comprehensive introduction to text mining using MATLAB. --
Text Mining With Matlab
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Author : Rafael E. Banchs
language : en
Publisher: Springer Nature
Release Date : 2021-10-21
Text Mining With Matlab written by Rafael E. Banchs and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-10-21 with Computers categories.
Text Mining with MATLAB® provides a comprehensive introduction to text mining using MATLAB. It is designed to help text mining practitioners, as well as those with little-to-no experience with text mining in general, familiarize themselves with MATLAB and its complex applications. The book is structured in three main parts: The first part, Fundamentals, introduces basic procedures and methods for manipulating and operating with text within the MATLAB programming environment. The second part of the book, Mathematical Models, is devoted to motivating, introducing, and explaining the two main paradigms of mathematical models most commonly used for representing text data: the statistical and the geometrical approach. Eventually, the third part of the book, Techniques and Applications, addresses general problems in text mining and natural language processing applications such as document categorization, document search, content analysis, summarization, question answering, and conversational systems. This second edition includes updates in line with the recently released “Text Analytics Toolbox” within the MATLAB product and introduces three new chapters and six new sections in existing ones. All descriptions presented are supported with practical examples that are fully reproducible. Further reading, as well as additional exercises and projects, are proposed at the end of each chapter for those readers interested in conducting further experimentation.
Exploratory Data Analysis With Matlab
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Author : Wendy L. Martinez
language : en
Publisher: CRC Press
Release Date : 2010-12-16
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 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
Text Mining With Machine Learning
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Author : Jan Žižka
language : en
Publisher: CRC Press
Release Date : 2019-10-31
Text Mining With Machine Learning written by Jan Žižka and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-10-31 with Computers categories.
This book provides a perspective on the application of machine learning-based methods in knowledge discovery from natural languages texts. By analysing various data sets, conclusions which are not normally evident, emerge and can be used for various purposes and applications. The book provides explanations of principles of time-proven machine learning algorithms applied in text mining together with step-by-step demonstrations of how to reveal the semantic contents in real-world datasets using the popular R-language with its implemented machine learning algorithms. The book is not only aimed at IT specialists, but is meant for a wider audience that needs to process big sets of text documents and has basic knowledge of the subject, e.g. e-mail service providers, online shoppers, librarians, etc. The book starts with an introduction to text-based natural language data processing and its goals and problems. It focuses on machine learning, presenting various algorithms with their use and possibilities, and reviews the positives and negatives. Beginning with the initial data pre-processing, a reader can follow the steps provided in the R-language including the subsuming of various available plug-ins into the resulting software tool. A big advantage is that R also contains many libraries implementing machine learning algorithms, so a reader can concentrate on the principal target without the need to implement the details of the algorithms her- or himself. To make sense of the results, the book also provides explanations of the algorithms, which supports the final evaluation and interpretation of the results. The examples are demonstrated using realworld data from commonly accessible Internet sources.
Matlab For Machine Learning
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Author : Giuseppe Ciaburro
language : en
Publisher:
Release Date : 2017-08-24
Matlab For Machine Learning written by Giuseppe Ciaburro and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-08-24 with categories.
Extract patterns and knowledge from your data in easy way using MATLABAbout This Book* Get your first steps into machine learning with the help of this easy-to-follow guide* Learn regression, clustering, classification, predictive analytics, artificial neural networks and more with MATLAB* Understand how your data works and identify hidden layers in the data with the power of machine learning.Who This Book Is ForThis book is for data analysts, data scientists, students, or anyone who is looking to get started with machine learning and want to build efficient data processing and predicting applications. A mathematical and statistical background will really help in following this book well.What You Will Learn* Learn the introductory concepts of machine learning.* Discover different ways to transform data using SAS XPORT, import and export tools,* Explore the different types of regression techniques such as simple & multiple linear regression, ordinary least squares estimation, correlations and how to apply them to your data.* Discover the basics of classification methods and how to implement Naive Bayes algorithm and Decision Trees in the Matlab environment.* Uncover how to use clustering methods like hierarchical clustering to grouping data using the similarity measures.* Know how to perform data fitting, pattern recognition, and clustering analysis with the help of MATLAB Neural Network Toolbox.* Learn feature selection and extraction for dimensionality reduction leading to improved performance.In DetailMATLAB is the language of choice for many researchers and mathematics experts for machine learning. This book will help you build a foundation in machine learning using MATLAB for beginners.You'll start by getting your system ready with t he MATLAB environment for machine learning and you'll see how to easily interact with the Matlab workspace. We'll then move on to data cleansing, mining and analyzing various data types in machine learning and you'll see how to display data values on a plot. Next, you'll get to know about the different types of regression techniques and how to apply them to your data using the MATLAB functions.You'll understand the basic concepts of neural networks and perform data fitting, pattern recognition, and clustering analysis. Finally, you'll explore feature selection and extraction techniques for dimensionality reduction for performance improvement.At the end of the book, you will learn to put it all together into real-world cases covering major machine learning algorithms and be comfortable in performing machine learning with MATLAB.Style and approachThe book takes a very comprehensive approach to enhance your understanding of machine learning using MATLAB. Sufficient real-world examples and use cases are included in the book to help you grasp the concepts quickly and apply them easily in your day-to-day work.
Computational Statistics Handbook With Matlab
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Author : Wendy L. Martinez
language : en
Publisher: CRC Press
Release Date : 2001-09-26
Computational Statistics Handbook 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 2001-09-26 with Mathematics categories.
Approaching computational statistics through its theoretical aspects can be daunting. Often intimidated or distracted by the theory, researchers and students can lose sight of the actual goals and applications of the subject. What they need are its key concepts, an understanding of its methods, experience with its implementation, and practice with
Computational Mathematics
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Author : Robert E. White
language : en
Publisher: CRC Press
Release Date : 2003-09-17
Computational Mathematics written by Robert E. White and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2003-09-17 with Mathematics categories.
Computational Mathematics: Models, Methods, and Analysis with MATLAB and MPI explores and illustrates this process. Each section of the first six chapters is motivated by a specific application. The author applies a model, selects a numerical method, implements computer simulations, and assesses the ensuing results. These chapters include an abundance of MATLAB code. By studying the code instead of using it as a "black box, " you take the first step toward more sophisticated numerical modeling. The last four chapters focus on multiprocessing algorithms implemented using message passing interface (MPI). These chapters include Fortran 9x codes that illustrate the basic MPI subroutines and revisit the applications of the previous chapters from a parallel implementation perspective. All of the codes are available for download from www4.ncsu.edu./~white. This book is not just about math, not just about computing, and not just about applications, but about all three--in other words, computational science. Whether used as an undergraduate textbook, for self-study, or for reference, it builds the foundation you need to make numerical modeling and simulation integral parts of your investigational toolbox.
Applied Optimization With Matlab Programming
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Author : P. Venkataraman
language : en
Publisher: John Wiley & Sons
Release Date : 2009-03-23
Applied Optimization With Matlab Programming written by P. Venkataraman and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2009-03-23 with Technology & Engineering categories.
Technology/Engineering/Mechanical Provides all the tools needed to begin solving optimization problems using MATLAB® The Second Edition of Applied Optimization with MATLAB® Programming enables readers to harness all the features of MATLAB® to solve optimization problems using a variety of linear and nonlinear design optimization techniques. By breaking down complex mathematical concepts into simple ideas and offering plenty of easy-to-follow examples, this text is an ideal introduction to the field. Examples come from all engineering disciplines as well as science, economics, operations research, and mathematics, helping readers understand how to apply optimization techniques to solve actual problems. This Second Edition has been thoroughly revised, incorporating current optimization techniques as well as the improved MATLAB® tools. Two important new features of the text are: Introduction to the scan and zoom method, providing a simple, effective technique that works for unconstrained, constrained, and global optimization problems New chapter, Hybrid Mathematics: An Application, using examples to illustrate how optimization can develop analytical or explicit solutions to differential systems and data-fitting problems Each chapter ends with a set of problems that give readers an opportunity to put their new skills into practice. Almost all of the numerical techniques covered in the text are supported by MATLAB® code, which readers can download on the text's companion Web site www.wiley.com/go/venkat2e and use to begin solving problems on their own. This text is recommended for upper-level undergraduate and graduate students in all areas of engineering as well as other disciplines that use optimization techniques to solve design problems.
Micromechatronics
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Author : Victor Giurgiutiu
language : en
Publisher: CRC Press
Release Date : 2011-05-19
Micromechatronics written by Victor Giurgiutiu and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2011-05-19 with Technology & Engineering categories.
Focusing on recent developments in engineering science, enabling hardware, advanced technologies, and software, Micromechatronics: Modeling, Analysis, and Design with MATLAB®, Second Edition provides clear, comprehensive coverage of mechatronic and electromechanical systems. It applies cornerstone fundamentals to the design of electromechanical systems, covers emerging software and hardware, introduces the rigorous theory, examines the design of high-performance systems, and helps develop problem-solving skills. Along with more streamlined material, this edition adds many new sections to existing chapters. New to the Second Edition Updated and extended worked examples along with the associated MATLAB® codes Additional problems and exercises at the end of many chapters New sections on MATLAB New case studies The book explores ways to improve and optimize a broad spectrum of electromechanical systems widely used in industrial, transportation, and power systems. It examines the design and analysis of high-performance mechatronic systems, energy systems, efficient energy conversion, power electronics, controls, induced-strain devices, active sensors, microcontrollers, and motion devices. The text also enables a deep understanding of the multidisciplinary underpinnings of engineering. It can be used for courses in mechatronics, power systems, energy systems, active materials and smart structures, solid-state actuation, structural health monitoring, and applied microcontroller engineering.
Computational Intelligence Applications For Text And Sentiment Data Analysis
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Author : Dipankar Das
language : en
Publisher: Academic Press
Release Date : 2023-07-14
Computational Intelligence Applications For Text And Sentiment Data Analysis written by Dipankar Das and has been published by Academic Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-07-14 with Computers categories.
Approx.330 pagesApprox.330 pages