Java Data Object

Well-known for its nontechnical style, this popular survival analysis textbook has been brought up to date with modern statistical techniques for handling survival data as well as new data sets and ex

Continual improvements in data collection and processing have had a huge impact on brain research, producing data sets that are often large and complicated. By emphasizing a few fundamental principles

Virtually all nontrivial and modern service related problems and systems involve data volumes and types that clearly fall into what is presently meant as "big data", that is, are huge, heterogeneous,

'Big data' poses challenges that require both classical multivariate methods and contemporary techniques from machine learning and engineering. This modern text equips you for the new world - integrating the old and the new, fusing theory and practice and bridging the gap to statistical learning. The theoretical framework includes formal statements that set out clearly the guaranteed 'safe operating zone' for the methods and allow you to assess whether data is in the zone, or near enough. Extensive examples showcase the strengths and limitations of different methods with small classical data, data from medicine, biology, marketing and finance, high-dimensional data from bioinformatics, functional data from proteomics, and simulated data. High-dimension low-sample-size data gets special attention. Several data sets are revisited repeatedly to allow comparison of methods. Generous use of colour, algorithms, Matlab code, and problem sets complete the package. Suitable for master's/graduat

Pattern recognition in data is a well known classical problem that falls under the ambit of data analysis. As we need to handle different data, the nature of patterns, their recognition and the types

"Panel Data Analysis using EViews provides graduate students, researchers, and statisticians with step-by-step guidance on how to apply EViews software to panel data analysis using appropriate empiric

This volume tackles the conflicting requirements of data compression and indexing in massive datasets, by using optimization techniques to improve compression and reconfiguring data structure to incre

Providing the knowledge and practical experience to begin analysing scientific data, this book is ideal for physical sciences students wishing to improve their data handling skills. The book focuses on explaining and developing the practice and understanding of basic statistical analysis, concentrating on a few core ideas, such as the visual display of information, modelling using the likelihood function, and simulating random data. Key concepts are developed through a combination of graphical explanations, worked examples, example computer code and case studies using real data. Students will develop an understanding of the ideas behind statistical methods and gain experience in applying them in practice. Further resources are available at www.cambridge.org/9781107607590, including data files for the case studies so students can practise analysing data, and exercises to test students' understanding.

Owing to continuous advances in the computational power of handheld devices like smartphones and tablet computers, it has become possible to perform Big Data operations including modern data mining pr

To tackle the challenges of Big Data, novel approaches and tools have emerged. Moreover, the technology required for big-data computing is developing at a satisfactory rate due to market forces and te

"This book discusses the exponential growth of information size and the innovative methods for data capture, storage, sharing, and analysis for big data"--

This book introduces the basic aspects of applied mathematics. It also covers such topics as information data manipulation, information coding, data approximation, data dimensionality reduction, data

The field of data mining has made significant and far-reaching advances over the past three decades. Because of its potential power for solving complex problems, data mining has been successfully appl

The burgeoning field of data analysis is expanding at an incredible pace due to the proliferation of data collection in almost every area of science. The enormous data sets now routinely encountered i

"Clustering is a diverse topic, and the underlying algorithms depend greatly on the data domain and problem scenario. This book focuses on three primary aspects of data clustering: the core methods su

Written for those with a science and engineering background, this book introduces and explains a comprehensive set of data mining techniques from various data mining fields. Concepts and methodologies

Over 70 countries and various international organizations have adopted data protection and privacy laws that regulate the cross-border transfer of personal data outside their borders. In an era of glo

This book is focused on the development of a data integration framework for retrieval of biodiversity information from heterogeneous and distributed data sources. The data integration system proposed

Despite research interest in functional data analysis in the last three decades, few books are available on the subject. Filling this gap, Analysis of Variance for Functional Data presents up-to-date

Data Mining Mobile Devices, also known as "Reality Mining," defines the collection of machine-sensed environmental data pertaining to human social behavior. This new paradigm of data mining makes poss

As organizations deploy business intelligence and analytic systems to harness business value from their data assets, data governance programs are quickly gaining prominence. And, although data managem

Provides examples of applications of object detection and recognition, along with the working examples of code for solutions to real computer vision problemsObject Detection and Recognition in Digital

This book offers a novel account of grace, framed in terms of Bruno Latour's "principle of irreduction." It thus models an object-oriented approach to grace, experimentally moving a traditional Christ

This work identifies developmental stages in the acquisition of object pronouns by instructed second language learners of Spanish.It examines learners ranging from beginner to advanced, where the most

The issue of data quality is as old as data itself. However, the proliferation of diverse, large-scale and often publically available data on the Web has increased the risk of poor data quality and mi

A major survey of Pop Art from private collections. Published on the occasion of an exhibition of the same title, The Pop Object is the most comprehensive survey of Pop Art to be organized by theme an

Intelligent data analysis techniques offer powerful solutions to collecting and analyzing vast quantities of environmental and economic data, which lead to better decision making for sustainable devel

This book opens discussion on the topics of data management. It is not a new topic at all because scientists deal with data every day; what makes this topic unique is the scale of data everyone is dea

With the purpose of building upon standard web technologies, open linked data serves as a useful way to connect previously unrelated data and to publish structured data on the web. The application of

A comprehensive source on mixed data analysis, Analysis of Mixed Data: Methods & Applications summarizes the fundamental developments in the field. Case studies are used extensively throughout the

This text is an unbound, binder-ready edition. Cay Horstmanns fifth edition of Big Java, Early Objectsprovides a comprehensive and approachable introduction to fundamental programming techniques and d

The series, Contemporary Perspectives on Data Mining, is composed of blind refereed scholarly research methods and applications of data mining. This series will be targeted both at the academic commun

On 25 January 2012, the European Commission presented its long awaited new “Data protection package”. With this proposal for a drastic revision of the data protection framework in Europe, it is fair t

For machine intelligence applications to work successfully, machines must perform reliably under variations of data and must be able to keep up with data streams. Internet-Scale Pattern Recognition: N

The Complete Book of Data Anonymization: From Planning to Implementation supplies a 360-degree view of data privacy protection using data anonymization. It examines data anonymization from both a prac

Unique insights to implement big data analytics and reap big returns to your bottom lineFocusing on the business and financial value of big data analytics, respected technology journalist Frank J. Ohl

The world is awash with digital data from social networks, blogs, business, science and engineering. Data-intensive computing facilitates understanding of complex problems that must process massive amounts of data. Through the development of new classes of software, algorithms and hardware, data-intensive applications can provide timely and meaningful analytical results in response to exponentially growing data complexity and associated analysis requirements. This emerging area brings many challenges that are different from traditional high-performance computing. This reference for computing professionals and researchers describes the dimensions of the field, the key challenges, the state of the art and the characteristics of likely approaches that future data-intensive problems will require. Chapters cover general principles and methods for designing such systems and for managing and analyzing the big data sets of today that live in the cloud and describe example applications in bioin

Each edition of Introduction to Data Compression has widely been considered the best introduction and reference text on the art and science of data compression, and the?fourth edition continues in thi

Drawing on the authors’ extensive research in the analysis of categorical longitudinal data, Latent Markov Models for Longitudinal Data focuses on the formulation of latent Markov models and the pract

This book covers important aspects of fundamental research in data provenance and data management(DPDM), including provenance representation and querying, as well as practical applications in such dom