The Tableau Workshop offers a comprehensive, hands-on guide to mastering data visualization with Tableau. Through practical exercises and engaging examples, you will learn how to prepare, analyze, and visualize data to uncover valuable business insights. By completing this book, you will confidently understand the key concepts and tools needed to create impactful data-driven visual stories. What this Book will help me do Master the use of Tableau Desktop and Tableau Prep for data visualization tasks. Gain the ability to prepare and process data for effective analysis. Learn to choose and utilize the most appropriate chart types for different scenarios. Develop the skills to create interactive dashboards that engage stakeholders. Understand how to perform calculations to extract deeper insights from data. Author(s) Sumit Gupta, None Pinto, Shweta Savale, JC Gillet None, and None Cherven are experts in the field of data analytics and visualization. With diverse backgrounds in business intelligence and hands-on experience with industry tools like Tableau, they bring valuable insights to this book. Their collaborative effort offers practical, real-world knowledge tailored to help learners excel in Tableau and data visualization. With their passion for making technical concepts accessible, they guide readers step by step through their learning journey. Who is it for? This book is ideal for professionals, analysts, or students looking to delve into the world of data visualization with Tableau. Whether you're a complete beginner seeking foundational knowledge, or an intermediate user aiming to refine your skills, this book offers the practical insights you need. It's designed for those who want to master Tableau tools, explore meaningful data insights, and effectively communicate them through engaging dashboards and stories.

This book aims to provide theoretical and empirical frameworks and highlights the challenges and solutions with using Big Data for Corporate Social Responsibility (CSR) and Sustainability in the field of digital transformation and tourism.

"Microsoft Power BI Performance Best Practices" is a thorough guide to mastering efficiently operating Power BI solutions. This book walks you through optimizing every layer of a Power BI project, from data transformations to architecture, equipping you with the ability to create robust and scalable analytics solutions. What this Book will help me do Understand how to set realistic performance goals for Power BI projects and implement ongoing performance monitoring. Apply effective architectural and configuration strategies to improve Power BI solution efficiency. Learn practices for constructing and optimizing data models and implementing Row-Level Security effectively. Utilize tools like DAX Studio and VertiPaq Analyzer to detect and resolve common performance bottlenecks. Gain deep knowledge of Power BI Premium and techniques for handling large-scale data solutions using Azure. Author(s) Bhavik Merchant is a recognized expert in business intelligence and analytics solutions. With extensive experience in designing and implementing Power BI solutions across industries, he brings a pragmatic approach to solving performance issues in Power BI. Bhavik's writing style reflects his passion for teaching, ensuring readers gain practical knowledge they can directly apply to their work. Who is it for? This book is designed for data analysts, BI developers, and data professionals who have foundational knowledge of Power BI and aim to elevate their skills to construct high-performance analytics solutions. It is particularly suited to individuals seeking guidance on best practices and tools for optimizing Power BI applications.

The Kaggle Book is an essential guide for anyone aiming to excel in data science through Kaggle competitions. With expert advice from Kaggle Grandmasters, you'll learn practical techniques for handling data, creating robust models, and improving your ranking in competitions. This book is packed with insights on advanced topics like ensembling, validation, and evaluation metrics. What this Book will help me do Master the Kaggle platform, including its Notebooks, Datasets, and Discussion capabilities. Enhance model performance using techniques like feature engineering, AutoML, and ensembling strategies. Apply advanced validation schemes to improve the reliability of your predictions. Tackle diverse competition types, including NLP, computer vision, and optimization challenges. Build a professional portfolio to showcase your data science expertise and attract career opportunities. Author(s) Konrad Banachewicz and Luca Massaron, authoritative Kaggle Grandmasters, bring their wealth of experience in competitive data science to this book. They have collectively competed in numerous Kaggle challenges and possess deep insights into what differentiates successful Kagglers. Their guidance combines practicality with expertise, making this book a must-have for aspiring data scientists looking to make an impact. Who is it for? This book is tailored for data analysts and scientists interested in enhancing their Kaggle performance, as well as those new to Kaggle who wish to explore competitive data science. It suits individuals with basic knowledge of machine learning, aiming to develop and demonstrate their skills further. The content is valuable for practitioners aiming to build a professional profile or secure roles in the tech industry.

BIOINFORMATICS AND MEDICAL APPLICATIONS The main topics addressed in this book are big data analytics problems in bioinformatics research such as microarray data analysis, sequence analysis, genomics-based analytics, disease network analysis, techniques for big data analytics, and health information technology. Bioinformatics and Medical Applications: Big Data Using Deep Learning Algorithms analyses massive biological datasets using computational approaches and the latest cutting-edge technologies to capture and interpret biological data. The book delivers various bioinformatics computational methods used to identify diseases at an early stage by assembling cutting-edge resources into a single collection designed to enlighten the reader on topics focusing on computer science, mathematics, and biology. In modern biology and medicine, bioinformatics is critical for data management. This book explains the bioinformatician’s important tools and examines how they are used to evaluate biological data and advance disease knowledge. The editors have curated a distinguished group of perceptive and concise chapters that presents the current state of medical treatments and systems and offers emerging solutions for a more personalized approach to healthcare. Applying deep learning techniques for data-driven solutions in health information allows automated analysis whose method can be more advantageous in supporting the problems arising from medical and health-related information. Audience The primary audience for the book includes specialists, researchers, postgraduates, designers, experts, and engineers, who are occupied with biometric research and security-related issues.

It’s time for some truly “Excel-lent” spreadsheet reporting Beneath the seemingly endless rows and columns of cells, the latest version of Microsoft Excel boasts an astonishing variety of features and capabilities. But how do you go about tapping into some of that power without spending all of your days becoming a spreadsheet guru? It’s easy. You grab a copy of the newest edition of Excel Dashboards & Reports For Dummies and get ready to blow the pants off your next presentation audience! With this book, you’ll learn how to transform those rows and columns of data into dynamic reports, dashboards, and visualizations. You’ll draw powerful new insights from your company’s numbers to share with your colleagues – and seem like the smartest person in the room while you’re doing it. Excel Dashboards & Reports For Dummies offers: Complete coverage of the latest version of Microsoft Excel provided in the Microsoft 365 subscription Strategies to automate your reporting so you don’t have to manually crunch the numbers every week, month, quarter, or year Ways to get new perspectives on old data, visualizing it so you can find solutions no one else has seen before If you’re ready to make your company’s numbers and spreadsheets dance, it’s time to get the book that’ll have them moving to your tune in no time. Get Excel Dashboards & Reports For Dummies today.

INTERNET OF MEDICAL THINGS (IOMT) Providing an essential addition to the reference material available in the field of IoMT, this timely publication covers a range of applied research on healthcare, biomedical data mining, and the security and privacy of health records. With their ability to collect, analyze and transmit health data, IoMT tools are rapidly changing healthcare delivery. For patients and clinicians, these applications are playing a central part in tracking and preventing chronic illnesses — and they are poised to evolve the future of care. In this book, the authors explore the potential applications of a wave of sensor-based tools—including wearables and stand-alone devices for remote patient monitoring—and the marriage of internet-connected medical devices with patient information that ultimately sets the IoMT ecosystem apart. This book demonstrates the connectivity between medical devices and sensors is streamlining clinical workflow management and leading to an overall improvement in patient care, both inside care facilities and in remote locations.

Compared to other functions of an organization, data science is highly speculative. Data science teams are often tasked with last-minute must-have deliverables that are well beyond their ability to produce. Data might be missing or have no signal, or the data models themselves might be impractical. This hands-on reference guides team leaders through the types of challenges you might face and the tools you need to work through them. Author Jacqueline Nolis, head of data science at Saturn Cloud, helps team leaders think through the various issues you'll encounter when running a data science team. You'll learn ways to set up your team, manage data scientists to promote their success, and collaborate with external stakeholders. Once you finish this report, you'll be ready to work through the challenges your current team faces or start a new data science team in an organization that needs one. Determine the scope of work before choosing your team of data scientists and support positions Successfully manage your relationship with stakeholders by providing your team with clear, achievable goals Create an environment to help data scientists and other team members succeed Choose a technical infrastructure for your team, including programming languages, databases, and deployment models

Dive into the world of reproducible data science with Pachyderm, a specialized platform designed for version-controlled data pipelines. By following this book, 'Reproducible Data Science with Pachyderm,' you'll gain the skills to implement robust, scalable machine learning workflows with Pachyderm 2.0, covering setup, integration, and advanced use cases. What this Book will help me do Build scalable, version-controlled data pipelines with Pachyderm's unique features. Understand the principles behind reproducible data science and implement them effectively. Deploy Pachyderm on AWS, Google Cloud, and Azure while integrating with popular tools. Create and manage end-to-end machine learning workflows, including hyperparameter tuning. Leverage advanced integrations, such as Pachyderm Notebooks and language clients like Python and Go. Author(s) Svetlana Karslioglu is a seasoned data scientist with extensive experience in constructing scalable machine learning and data processing systems. With years in both practical implementation and educational endeavors, she has a talent for breaking down complex concepts into accessible learning paths. Her approach is hands-on and results-oriented, aimed at empowering professionals to excel in the field of data science. Who is it for? This book is intended for data scientists, machine learning engineers, and data engineers who are keen to ensure reproducibility in their workflows. Ideal readers may have familiarity with data science basics and some exposure to Kubernetes and programming languages like Python. By studying the book, learners will establish confidence in implementing Pachyderm for scalable and reliable data pipelines.

This handy reference book detailing the intricacies of R covers version 4.x features, including numerous and significant changes to syntax, strings, reference counting, grid units, and more. Starting with the basic structure of R, the book takes you on a journey through the terminology used in R and the syntax required to make R work. You will find looking up the correct form for an expression quick and easy. Some of the new material includes information on RStudio, S4 syntax, working with character strings, and an example using the Twitter API. With a copy of the R 4 Quick Syntax Reference in hand, you will find that you are able to use the multitude of functions available in R and are even able to write your own functions to explore and analyze data. What You Will Learn Discover the modes and classes of R objects and how to use them Use both packaged and user-created functions in R Import/export data and create new data objects in R Create descriptive functions and manipulate objects in R Take advantage of flow control and conditional statements Work with packages such as base, stats, and graphics Who This Book Is For Those with programming experience, either new to R, or those with at least some exposure to R but who are new to the latest version.

The essential, intermediate and advanced topics of Simulink are covered in the book. The concept of multi-domain physical modeling concept and tools in Simulink are illustrated with examples for engineering systems and multimedia information. The combination of Simulink and numerical optimization methods provides new approaches for solving problems, where solutions are not known otherwise.

From an Alexa device in our home to an aircraft, Cyber-Physical Systems (CPS) have transformed the living standard of human beings. The data generated from the CPS provide tremendous insights into the behaviour and functioning of organisations.

Learn to crunch huge amounts of data with PowerPivot and Power Query Do you have a ton of data you need to make sense of? Microsoft’s Excel program can handle amazingly large data sets, but you’ll need to get familiar with PowerPivot and Power Query to get started. And that’s where Dummies comes in. With step-by-step instructions—accompanied by ample screenshots—Excel PowerPivot & Power Query For Dummies will teach you how to save time, simplify your processes, and enhance your data analysis and reporting. Use Power Query to discover, connect to, and import your organization’s data. Then use PowerPivot to model it in Excel. You’ll also learn to: Make use of databases to store large amounts of data Use custom functions to extend and enhance Power Query Add the functionality of formulas to PowerPivot and publish data to SharePoint If you’re expected to wrangle, interpret, and report on large amounts of data, Excel PowerPivot & Power Query For Dummies gives you the tools you need to get up to speed quickly.

Time Series Analysis on AWS is your guide to building and deploying powerful forecasting models and identifying anomalies in your time series data. With this book, you will explore effective strategies for modern time series analysis using Amazon Web Services' powerful AI/ML tools. What this Book will help me do Master the fundamental concepts of time series and its applications using industry-relevant examples. Understand time series forecasting with Amazon Forecast and how to deliver actionable business insights. Build and deploy anomaly detection systems using Amazon Lookout for Equipment for predictive maintenance. Learn to utilize Amazon Lookout for Metrics to identify business operational anomalies effectively. Gain practical experience applying AWS ML tools to real-world time series data challenges. Author(s) None Hoarau is a data scientist with extensive experience in utilizing machine learning to solve real-world problems. Combining strong programming skills with domain expertise, they focus on developing applications leveraging AWS AI services. This book reflects their passion for making technical topics accessible and actionable for professionals. Who is it for? This book is ideal for data analysts, business analysts, and data scientists eager to enhance their skills in time series analysis. It suits readers familiar with statistical concepts but new to machine learning. If you're aiming to solve business problems using data and AWS tools, this resource is tailored for you.

Discover how to build decision trees using SAS Viya ! Tree-Based Machine Learning Methods in SAS Viya covers everything from using a single tree to more advanced bagging and boosting ensemble methods. The book includes discussions of tree-structured predictive models and the methodology for growing, pruning, and assessing decision trees, forests, and gradient boosted trees. Each chapter introduces a new data concern and then walks you through tweaking the modeling approach, modifying the properties, and changing the hyperparameters, thus building an effective tree-based machine learning model. Along the way, you will gain experience making decision trees, forests, and gradient boosted trees that work for you. By the end of this book, you will know how to: build tree-structured models, including classification trees and regression trees. build tree-based ensemble models, including forest and gradient boosting. run isolation forest and Poisson and Tweedy gradient boosted regression tree models. implement open source in SAS and SAS in open source. use decision trees for exploratory data analysis, dimension reduction, and missing value imputation.

Learn Power BI is a comprehensive guide to mastering Microsoft Power BI. With step-by-step instructions, this book equips you to analyze and visualize data effectively, delivering actionable business insights. Whether you're new to Power BI or seeking to deepen your knowledge, you'll find practical examples and hands-on exercises to enhance your skills. What this Book will help me do Master the basics of using Microsoft Power BI for data analysis. Learn to clean and transform datasets effectively using Power Query. Build analytical models and perform calculations using DAX. Design professional-quality reports, dashboards, and visualizations. Understand governance and deploy Power BI in organizational environments. Author(s) Greg Deckler is a recognized expert in business intelligence and analytics, bringing years of practical experience in using Microsoft Power BI for data-driven decision-making. As an accomplished author, Greg's approachable writing style helps readers of all levels. In his book, he conveys complex concepts in a clear, structured, and user-friendly manner. Who is it for? This book is ideal for IT professionals, data analysts, and individuals interested in business intelligence using Power BI. Whether you're a beginner or transitioning from other tools, it guides you through the basics to advanced features. If you want to harness Power BI to create impactful reports or dashboards, this book is for you.

Discover the power of Amazon QuickSight with this comprehensive guide. Learn to create stunning data visualizations, integrate machine learning insights, and automate operations to optimize your data analytics workflows. This book offers practical guidance on utilizing QuickSight to develop insightful and interactive business intelligence solutions. What this Book will help me do Understand the role of Amazon QuickSight within the AWS analytics ecosystem. Learn to configure data sources and develop visualizations effectively. Gain skills in adding interactivity to dashboards using custom controls and parameters. Incorporate machine learning capabilities into your dashboards, including forecasting and anomaly detection. Explore advanced features like QuickSight APIs and embedded multi-tenant analytics design. Author(s) None Samatas is an AWS-certified big data solutions architect with years of experience in designing and implementing scalable analytics solutions. With a clear and practical approach, None teaches how to effectively leverage Amazon QuickSight for efficient and insightful business intelligence applications. Their expertise ensures readers will gain actionable skills. Who is it for? This book is ideal for business intelligence (BI) developers and data analysts looking to deepen their expertise in creating interactive dashboards using Amazon QuickSight. It is a perfect guide for professionals aiming to explore machine learning integration in BI solutions. Familiarity with basic data visualization concepts is recommended, but no prior experience with Amazon QuickSight is needed.

The goal for this book is to provide a step-by-step guide to the data science process so that you can feel confident in leading your own data science project. To aid with clarity and understanding, the author presents a fictional restaurant chain to use as a case study -- it illustrates how the various topics discussed can be applied.

IoT-Enabled Smart Healthcare Systems, Services and Applications Explore the latest healthcare applications of cutting-edge technologies In IoT-Enabled Smart Healthcare Systems, Services and Applications, an accomplished team of researchers delivers an insightful and comprehensive exploration of the roles played by cutting-edge technologies in modern healthcare delivery. The distinguished editors have included resources from a diverse array of learned experts in the field that combine to create a broad examination of a rapidly developing field. With a particular focus on Internet of Things (IoT) technologies, readers will discover how new technologies are impacting healthcare applications from remote monitoring systems to entire healthcare delivery methodologies. After an introduction to the role of emerging technologies in smart health care, this volume includes treatments of ICN-Fog computing, edge computing, security and privacy, IoT architecture, vehicular ad-hoc networks (VANETs), and patient surveillance systems, all in the context of healthcare delivery. Readers will also find: A thorough introduction to ICN-Fog computing for IoT based healthcare, including its architecture and challenges Comprehensive explorations of Internet of Things enabled software defined networking for edge computing in healthcare Practical discussions of a review of e-healthcare systems in India and Thailand, as well as the security and privacy issues that arise through the use of smart healthcare systems using Internet of Things devices In-depth examinations of the architecture and applications of an Internet of Things based healthcare system Perfect for healthcare practitioners and allied health professionals, hospital administrators, and technology professionals, IoT-Enabled Smart Healthcare Systems, Services and Applications is an indispensable addition to the libraries of healthcare regulators and policymakers seeking a one-stop resource that explains cutting-edge technologies in modern healthcare.

Causal inference lies at the heart of our ability to understand why things happen by helping us predict the results of our actions. This process is vital for businesses that aspire to turn data and information into valuable knowledge. With this report, data scientists and analysts will learn a principled way of thinking about causality, using a suite of causal inference techniques now available. Authors Hugo Bowne-Anderson, a data science consultant, and Mike Loukides, vice president of content strategy at O'Reilly Media, introduce causality and discuss randomized control trials (RCTs), key aspects of causal graph theory, and much-needed techniques from econometrics. You'll explore: Techniques from econometrics, including randomized control trials, the causality gold standard used in A/B-testing The constant-effects model for dealing with all things not being equal across the groups you're comparing Regression for dealing with confounding variables and selection bias Instrumental variables to estimate causal relationships in situations where regression won't work Techniques from causal graph theory including forks and colliders, the graphical tools for representing common causal patterns Backdoor and front-door adjustments for making causal inferences in the presence of confounders

Delve into advanced Data Analysis Expressions (DAX) concepts and Power BI capabilities with Extreme DAX, designed to elevate your skills in Microsoft's Business Intelligence tools. This book guides you through solving intricate business problems, improving your reporting, and leveraging data modeling principles to their fullest potential. What this Book will help me do Master advanced DAX functions and leverage their full potential in data analysis. Develop a solid understanding of context and filtering within Power BI models. Employ strategies for dynamic visualizations and secure data access via row-level security. Apply financial DAX functions for precise investment evaluations and forecasts. Utilize alternative calendars and advanced time-intelligence for comprehensive temporal analyses. Author(s) Michiel Rozema and Henk Vlootman bring decades of deep experience in data analytics and business intelligence to your learning journey. Both authors are seasoned practitioners in using DAX and Microsoft BI tools, with numerous practical deployments of their expertise in business solutions. Their approachable writing reflects their teaching style, ensuring you can easily grasp even challenging concepts. This book combines their comprehensive technical knowledge with real-world, hands-on examples, offering an invaluable resource for refining your skills. Who is it for? This book is perfect for intermediate to advanced analysts who have a foundational knowledge of DAX and Power BI and wish to deepen their expertise. If you are striving to improve performance and accuracy in your reports or aiming to handle advanced modeling scenarios, this book is for you. Prior experience with DAX, Power BI, or equivalent analytical tools is recommended to maximize the benefit. Whether you're a business analyst, data professional, or enthusiast, this book will elevate your analytical capabilities to new heights.

We are entering the era of digital transformation where human and artificial intelligence (AI) work hand in hand to achieve data driven performance. Today, more than ever, businesses are expected to possess the talent, tools, processes, and capabilities to enable their organizations to implement and utilize continuous analysis of past business performance and events to gain forward-looking insight to drive business decisions and actions. AI-Enabled Analytics in Business is your Roadmap to meet this essential business capability. To ensure we can plan for the future vs react to the future when it arrives, we need to develop and deploy a toolbox of tools, techniques, and effective processes to reveal forward-looking unbiased insights that help us understand significant patterns, relationships, and trends. This book promotes clarity to enable you to make better decisions from insights about the future. Learn how advanced analytics ensures that your people have the right information at the right time to gain critical insights and performance opportunities Empower better, smarter decision making by implementing AI-enabled analytics decision support tools Uncover patterns and insights in data, and discover facts about your business that will unlock greater performance Gain inspiration from practical examples and use cases showing how to move your business toward AI-Enabled decision making AI-Enabled Analytics in Business is a must-have practical resource for directors, officers, and executives across various functional disciplines who seek increased business performance and valuation.

Become a stats superstar by using Excel to reveal the powerful secrets of statistics Microsoft Excel offers numerous possibilities for statistical analysis—and you don’t have to be a math wizard to unlock them. In Statistical Analysis with Excel For Dummies, fully updated for the 2021 version of Excel, you’ll hit the ground running with straightforward techniques and practical guidance to unlock the power of statistics in Excel. Bypass unnecessary jargon and skip right to mastering formulas, functions, charts, probabilities, distributions, and correlations. Written for professionals and students without a background in statistics or math, you’ll learn to create, interpret, and translate statistics—and have fun doing it! In this book you’ll find out how to: Understand, describe, and summarize any kind of data, from sports stats to sales figures Confidently draw conclusions from your analyses, make accurate predictions, and calculate correlations Model the probabilities of future outcomes based on past data Perform statistical analysis on any platform: Windows, Mac, or iPad Access additional resources and practice templates through Dummies.com For anyone who’s ever wanted to unleash the full potential of statistical analysis in Excel—and impress your colleagues or classmates along the way—Statistical Analysis with Excel For Dummies walks you through the foundational concepts of analyzing statistics and the step-by-step methods you use to apply them.

In recent years, scientific research and translation medicine have placed increased emphasis on computational methodology and data curation across many disciplines, both to advance underlying science and to instantiate precision-medicine protocols in the lab and in clinical practice. The nexus of concerns related to oncology, cardiology, and virology (SARS-CoV-2) presents a fortuitous context within which to examine the theory and practice of biomedical data curation. Innovative Data Integration and Conceptual Space Modeling for COVID, Cancer, and Cardiac Care argues that a well-rounded approach to data modeling should optimally embrace multiple perspectives inasmuch as data-modeling is neither a purely formal nor a purely conceptual discipline, but rather a hybrid of both. On the one hand, data models are designed for use by computer software components, and are, consequently, constrained by the mechanistic demands of software environments; data modeling strategies must accept the formal rigors imposed by unambiguous data-sharing and query-evaluation logic. In particular, data models are not well-suited for software-level deployment if such models do not translate seamlessly to clear strategies for querying data and ensuring data integrity as information is moved across multiple points. On the other hand, data modeling is, likewise, constrained by human conceptual tendencies, because the information which is managed by databases and data networks is ultimately intended to be visualized/utilized by humans as the end-user. Thus, at the intersection of both formal and humanistic methodology, data modeling takes on elements of both logico-mathematical frameworks (e.g., type systems and graph theory) and conceptual/philosophical paradigms (e.g., linguistics and cognitive science). The authors embrace this two-sided aspect of data models by seeking non-reductionistic points of convergence between formal and humanistic/conceptual viewpoints, and by leveraging biomedical contexts (viz., COVID, Cancer, and Cardiac Care) so as to provide motivating examples and case-studies in this volume. Provides an analysis of how conceptual spaces and related cognitive linguistic approaches can inspire programming and query-processing models Outlines the vital role that data modeling/curation has played in significant medical breakthroughs Presents readers with an overview of how information-management approaches intersect with precision medicine, providing case studies of data-modeling in concrete scientific practice Explores applications of image analysis and computer vision in the context of precision medicine Examines the role of technology in scientific publishing, replication studies, and dataset curation

Change Detection and Image Time Series Analysis 1 presents a wide range of unsupervised methods for temporal evolution analysis through the use of image time series associated with optical and/or synthetic aperture radar acquisition modalities. Chapter 1 introduces two unsupervised approaches to multiple-change detection in bi-temporal multivariate images, with Chapters 2 and 3 addressing change detection in image time series in the context of the statistical analysis of covariance matrices. Chapter 4 focuses on wavelets and convolutional-neural filters for feature extraction and entropy-based anomaly detection, and Chapter 5 deals with a number of metrics such as cross correlation ratios and the Hausdorff distance for variational analysis of the state of snow. Chapter 6 presents a fractional dynamic stochastic field model for spatio temporal forecasting and for monitoring fast-moving meteorological events such as cyclones. Chapter 7 proposes an analysis based on characteristic points for texture modeling, in the context of graph theory, and Chapter 8 focuses on detecting new land cover types by classification-based change detection or feature/pixel based change detection. Chapter 9 focuses on the modeling of classes in the difference image and derives a multiclass model for this difference image in the context of change vector analysis.