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Book search results for Data cluster

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     Finding Groups in Data: An Introduction to Cluster Analysis (Wiley Series in Probability and Statistics)
Publisher: Wiley-Interscience
Author(s): Leonard Kaufman, Peter J. Rousseeuw

The Wiley-Interscience Paperback Series consists of selected books that have been made more accessible to consumers in an effort to increase global appeal and general circulation. With these new unabridged softcover volumes, Wiley hopes to extend the lives of these works by making them available to future generations of statisticians, mathematicians, and scientists.

"Cluster analysis is the increasingly important and practical subject of finding groupings in data. The authors set out to write a book for the user who does not necessarily have an extensive background in mathematics. They succeed very well."
?Mathematical Reviews

"Finding Groups in Data [is] a clear, readable, and interesting presentation of a small number of clustering methods. In addition, the book introduced some interesting innovations of applied value to clustering literature."
?Journal of Classification

"This is a very good, easy-to-read, and practical book. It has many nice features and is highly recommended for students and practitioners in various fields of study."
?Technometrics

An introduction to the practical application of cluster analysis, this text presents a selection of methods that together can deal with most applications. These methods are chosen for their robustness, consistency, and general applicability. This book discusses various types of data, including interval-scaled and binary variables as well as similarity data, and explains how these can be transformed prior to clustering.

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     MySQL High Availability: Tools for Building Robust Data Centers
Publisher: O'Reilly Media
Author(s): Charles Bell, Mats Kindahl, Lars Thalmann

Server bottlenecks and failures are a fact of life in any database deployment, but they don't have to bring everything to a halt. MySQL has several features that can help you protect your system from outages, whether it's running on hardware, virtual machines, or in the cloud. MySQL High Availability explains how to use these replication, cluster, and monitoring features in a wide range of real-life situations.

Written by engineers who designed many of the tools covered inside, this book reveals undocumented or hard-to-find aspects of MySQL reliability and high availability -- knowledge that?s essential for any organization using this database system.

  • Explore the binary log, a file for replication that helps in disaster recovery and troubleshooting
  • Get techniques for improving response time and handling large data sets
  • Monitor database activity and performance, as well as major operating system parameters
  • Keep track of what masters and slaves are doing, and deal with failures and restarts, corruption, and other incidents
  • Automate key tasks with code from an open source library written by the authors
  • Learn techniques for using MySQL in virtualized environments, such as Amazon Web Services
  • Use MySQL Cluster to achieve high availability
"MySQL replication is widely deployed but has never been adequately explained. This book changes that." -- Mark Callaghan, MySQL contributor and leader of MySQL engineering efforts at a few of the world's largest Internet companies


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     Oracle Database 11g Release 2 High Availability: Maximize Your Availability with Grid Infrastructure, RAC and Data Guard
Publisher: McGraw-Hill Osborne Media
Author(s): Scott Jesse, Bill Burton, Bryan Vongray

Leverage Oracle Database 11g Release 2 High Availability Features

Protect your critical business assets and achieve maximum database uptime using the detailed information in this Oracle Press guide. Oracle Database 11g Release 2 High Availability: Maximize Your Availability with Grid Infrastructure, Oracle Real Application Clusters, and Oracle Data Guard, Second Edition provides cost-effective solutions to current availability challenges. Discover how to grid-enable your IT framework, roll out Oracle Real Application Clusters, maintain standby databases, and deploy Oracle Flashback. Monitoring, tuning, and disaster recovery techniques are also covered in this comprehensive resource.

  • Install Oracle Clusterware (as part of Oracle's grid infrastructure) or upgrade from an earlier version
  • Build test clusters and hosts using Oracle VM
  • Work with Oracle Automatic Storage Management and Oracle Automatic Storage Management Cluster File System
  • Create synchronized standby databases using Oracle Data Guard
  • Reliably archive and restore data with Oracle Recovery Manager
  • Use Oracle Flashback to identify and undo user errors
  • Configure Oracle Enterprise Manager Grid Control for management of an Oracle maximum availability architecture environment


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     Data-Driven Marketing: The 15 Metrics Everyone in Marketing Should Know
Publisher: Wiley
Author(s): Mark Jeffery

NAMED BEST MARKETING BOOK OF 2011 BY THE AMERICAN MARKETING ASSOCIATION

How organizations can deliver significant performance gains through strategic investment in marketing

In the new era of tight marketing budgets, no organization can continue to spend on marketing without knowing what's working and what's wasted. Data-driven marketing improves efficiency and effectiveness of marketing expenditures across the spectrum of marketing activities from branding and awareness, trail and loyalty, to new product launch and Internet marketing. Based on new research from the Kellogg School of Management, this book is a clear and convincing guide to using a more rigorous, data-driven strategic approach to deliver significant performance gains from your marketing.

  • Explains how to use data-driven marketing to deliver return on marketing investment (ROMI) in any organization
  • In-depth discussion of the fifteen key metrics every marketer should know
  • Based on original research from America's leading marketing business school, complemented by experience teaching ROMI to executives at Microsoft, DuPont, Nisan, Philips, Sony and many other firms
  • Uses data from a rigorous survey on strategic marketing performance management of 252 Fortune 1000 firms, capturing $53 billion of annual marketing spending
  • In-depth examples of how to apply the principles in small and large organizations
  • Free downloadable ROMI templates for all examples given in the book

With every department under the microscope looking for results, those who properly use data to optimize their marketing are going to come out on top every time.

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     Data Clustering: Theory, Algorithms, and Applications (ASA-SIAM Series on Statistics and Applied Probability)
Publisher: SIAM, Society for Industrial and Applied Mathematics
Author(s): Guojun Gan, Chaoqun Ma, Jianhong Wu

Cluster analysis is an unsupervised process that divides a set of objects into homogeneous groups. This book starts with basic information on cluster analysis, including the classification of data and the corresponding similarity measures, followed by the presentation of over 50 clustering algorithms in groups according to some specific baseline methodologies such as hierarchical, center-based, and search-based methods. As a result, readers and users can easily identify an appropriate algorithm for their applications and compare novel ideas with existing results. The book also provides examples of clustering applications to illustrate the advantages and shortcomings of different clustering architectures and algorithms. Application areas include pattern recognition, artificial intelligence, information technology, image processing, biology, psychology, and marketing. Readers also learn how to perform cluster analysis with the C/C++ and MATLAB® programming languages. Audience The following groups will find this book a valuable tool and reference: applied statisticians; engineers and scientists using data analysis; researchers in pattern recognition, artificial intelligence, machine learning, and data mining; and applied mathematicians. Instructors can also use it as a textbook for an introductory course in cluster analysis or as source material for a graduate-level introduction to data mining. Contents Preface; Chapter 1: Data Clustering; Chapter 2: Data Types; Chapter 3: Scale Conversion; Chapter 4: Data Standardizatin and Transformation; Chapter 5: Data Visualization; Chapter 6: Similarity and Dissimilarity Measures; Chapter 7: Hierarchical Clustering Techniques; Chapter 8: Fuzzy Clustering Algorithms; Chapter 9: Center Based Clustering Algorithms; Chapter 10: Search Based Clustering Algorithms; Chapter 11: Graph Based Clustering Algorithms; Chatper 12: Grid Based Clustering Algorithms; Chapter 13: Density Based Clustering Algorithms; Chapter 14: Model Based Clustering Algorithms; Chapter 15: Subspace Clustering; Chapter 16: Miscellaneous Algorithms; Chapter 17: Evaluation of Clustering Algorithms; Chapter 18: Clustering Gene Expression Data; Chapter 19: Data Clustering in MATLAB; Chapter 20: Clustering in C/C++; Appendix A: Some Clustering Algorithms; Appendix B: Thekd-tree Data Structure; Appendix C: MATLAB Codes; Appendix D: C++ Codes; Subject Index; Author Index

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     In Search of Clusters (2nd Edition)
Publisher: Prentice Hall
Author(s): Gregory Pfister

As Microsoft's much-touted "Wolfpack" Cluster Server shows, clustering technology has arrived in the marketplace. Clustering is now a strategic direction for Microsoft, Compaq, IBM, Sun, DEC, Novell, and every other large computer company ? and their products are rolling out now. This comprehensive, highly-readable guide helps you make sense of clustering in all its forms, not just a single company's offering. Gregory Pfister ? one of the world's most respected experts on clustering technology ? delivers all the information you need to make critical strategic decisions. He introduces the primary hardware and software technologies involved in clusters, and shows why they have become popular ? and will become increasingly important. He presents the background that system planners, purchasers, designers and architects need to make effective use of clustering. He compares different types of clusters and the workloads they are best used for. He presents a detailed comparison of clusters with symmetric multiprocessing -- demonstrating major differences that are often "papered over." The book contains extensive new coverage of availability issues, as well as detailed coverage of Non-Uniform Memory Access (NUMA), the technology at the heart of new offerings from Sequent, HP, Pyramid, NCR and others. "Pfister is a prophet with an attitude..." ? Norris Parker Smith, HPCWire.



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     Cluster Randomised Trials (Chapman & Hall/CRC Interdisciplinary Statistics)
Publisher: Chapman and Hall/CRC
Author(s): Richard J. Hayes, Lawrence H. Moulton

Cluster Randomised Trials discusses the design, conduct, and analysis of health trials that randomise groups of individuals to different treatments. It explores the advantages of cluster randomization, with special attention given to evaluating the effects of interventions against infectious diseases.

Avoiding unnecessary mathematical detail, the book covers basic concepts underlying the use of cluster randomisation, such as direct, indirect, and total effects. The authors also present an array of design issues in cluster randomised trials (CRTs), including strategies for minimizing contamination effects, the use of stratification and restricted randomisation to improve balance between treatment arms, special methods for sample size calculation, and alternatives to the simplest two-arm CRT. After covering analytical methods for CRTs, such as regression methods, the authors examine ethical issues, trial monitoring, interim analyses, reporting, and interpretation.

Although the book mainly focuses on medical and public health applications, it shows that the rigorous evidence of intervention effects provided by CRTs has the potential to inform public policy in a wide range of other areas. The book encourages readers to apply the methods to their own trials, reproduce the analyses presented, and explore alternative approaches.



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     Practical Multivariate Analysis, Fifth Edition (Chapman & Hall/CRC Texts in Statistical Science)
Publisher: Chapman and Hall/CRC
Author(s): Abdelmonem Afifi, Susanne May, Virginia A. Clark

This new version of the bestselling Computer-Aided Multivariate Analysis has been appropriately renamed to better characterize the nature of the book. Taking into account novel multivariate analyses as well as new options for many standard methods, Practical Multivariate Analysis, Fifth Edition shows readers how to perform multivariate statistical analyses and understand the results. For each of the techniques presented in this edition, the authors use the most recent software versions available and discuss the most modern ways of performing the analysis.

New to the Fifth Edition

  • Chapter on regression of correlated outcomes resulting from clustered or longitudinal samples
  • Reorganization of the chapter on data analysis preparation to reflect current software packages
  • Use of R statistical software
  • Updated and reorganized references and summary tables
  • Additional end-of-chapter problems and data sets

The first part of the book provides examples of studies requiring multivariate analysis techniques; discusses characterizing data for analysis, computer programs, data entry, data management, data clean-up, missing values, and transformations; and presents a rough guide to assist in choosing the appropriate multivariate analysis. The second part examines outliers and diagnostics in simple linear regression and looks at how multiple linear regression is employed in practice and as a foundation for understanding a variety of concepts. The final part deals with the core of multivariate analysis, covering canonical correlation, discriminant, logistic regression, survival, principal components, factor, cluster, and log-linear analyses.

While the text focuses on the use of R, S-PLUS, SAS, SPSS, Stata, and STATISTICA, other software packages can also be used since the output of most standard statistical programs is explained. Data sets and code are available for download from the book?s web page and CRC Press Online.



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     Blueprints for High Availability
Publisher: Wiley
Author(s): Evan Marcus, Hal Stern

Expert techniques for designing your system to achieve maximum availability and predictable downtime

With your company's reputation and profits at stake, downtime on your 24/7 web site is not an option, nor is poor application performance. Now in its second edition, this authoritative book provides you with the design blueprints to maximize your system availability.

Striking a balance between costs and benefits, the authors show you all of the elements of your computer system that can fail-as well as ways to assess their reliability and attain resiliency and high availability for each one. A unique feature is "Tales from the Field," a collection of true-to-life experiences that will help you avoid mistakes and deploy your system with confidence.

Learn how to design your system to limit the impact of such problems as computer viruses, natural disasters, or the corruption of critical files and discover how to:
* Implement effective backup-and-restore and tape management strategies
* Arrange disks and disk arrays to avoid downtime caused by inevitable failures
* Utilize technologies such as Storage Area Networks (SANs), Network Attached Storage (NAS), Virtualization, and clustering
* Achieve effective application recovery after any part of the system has failed
* Replicate critical data to remote systems across a network

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     Shared Data Clusters: Scaleable, Manageable, and Highly Available Systems (VERITAS Series)
Publisher: Wiley
Author(s): Dilip M. Ranade

Clustering is a vital methodology in the data storage world. Its goal is to maximize cost-effectiveness, availability, flexibility, and scalability. Clustering has changed considerably for the better due to Storage Area Networks, which provide access to data from any node in the cluster.
  • Explains how clusters with shared storage work and the components in the cluster that need to work together
  • Reviews where a cluster should be deployed and how to use one for best performance
  • Author is Lead Technical Engineer for VERITAS Cluster File Systems and has worked on clusters and file systems for the past ten years


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     Oracle Database 11g Oracle Real Application Clusters Handbook, 2nd Edition (Oracle Press)
Publisher: McGraw-Hill Osborne Media
Author(s): K Gopalakrishnan

Master Oracle Real Application Clusters

Maintain a dynamic enterprise computing infrastructure with expert instruction from an Oracle ACE. Oracle Database 11g Oracle Real Application Clusters Handbook, Second Edition has been fully revised and updated to cover the latest tools and features. Find out how to prepare your hardware, deploy Oracle Real Application Clusters, optimize data integrity, and integrate seamless failover protection. Troubleshooting, performance tuning, and application development are also discussed in this comprehensive Oracle Press guide.

  • Install and configure Oracle Real Application Clusters
  • Configure and manage diskgroups using Oracle Automatic Storage Management
  • Work with services, voting disks, and Oracle Clusterware Repository
  • Look under the hood of the Cache Fusion and Global Resource Directory operations in Oracle Real Applications Clusters
  • Explore the internal workings of backup and recovery in Oracle Real Application Clusters
  • Employ workload balancing and the Transparent Application Failover feature of an Oracle database
  • Get complete coverage of Stretch Clusters, also known as Metro Clusters
  • Troubleshoot Oracle Clusterware using the most advanced diagnostics available
  • Develop custom Oracle Real Application Clusters applications



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     Exploratory Multivariate Analysis by Example Using R (Chapman & Hall/CRC Computer Science & Data Analysis)
Publisher: CRC Press
Author(s): Francois Husson, Sebastien Le, Jerome Pages

Full of real-world case studies and practical advice, Exploratory Multivariate Analysis by Example Using R focuses on four fundamental methods of multivariate exploratory data analysis that are most suitable for applications. It covers principal component analysis (PCA) when variables are quantitative, correspondence analysis (CA) and multiple correspondence analysis (MCA) when variables are categorical, and hierarchical cluster analysis.

The authors take a geometric point of view that provides a unified vision for exploring multivariate data tables. Within this framework, they present the principles, indicators, and ways of representing and visualizing objects that are common to the exploratory methods. The authors show how to use categorical variables in a PCA context in which variables are quantitative, how to handle more than two categorical variables in a CA context in which there are originally two variables, and how to add quantitative variables in an MCA context in which variables are categorical. They also illustrate the methods and the ways they can be exploited using examples from various fields.

Throughout the text, each result correlates with an R command accessible in the FactoMineR package developed by the authors. All of the data sets and code are available at http://factominer.free.fr/book

By using the theory, examples, and software presented in this book, readers will be fully equipped to tackle real-life multivariate data.



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     Advances in Machine Learning and Data Mining for Astronomy (Chapman & Hall/CRC Data Mining and Knowledge Discovery Series)
Publisher: Chapman and Hall/CRC
Author(s):

Advances in Machine Learning and Data Mining for Astronomy documents numerous successful collaborations among computer scientists, statisticians, and astronomers who illustrate the application of state-of-the-art machine learning and data mining techniques in astronomy. Due to the massive amount and complexity of data in most scientific disciplines, the material discussed in this text transcends traditional boundaries between various areas in the sciences and computer science.

The book?s introductory part provides context to issues in the astronomical sciences that are also important to health, social, and physical sciences, particularly probabilistic and statistical aspects of classification and cluster analysis. The next part describes a number of astrophysics case studies that leverage a range of machine learning and data mining technologies. In the last part, developers of algorithms and practitioners of machine learning and data mining show how these tools and techniques are used in astronomical applications.

With contributions from leading astronomers and computer scientists, this book is a practical guide to many of the most important developments in machine learning, data mining, and statistics. It explores how these advances can solve current and future problems in astronomy and looks at how they could lead to the creation of entirely new algorithms within the data mining community.



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     Categorical Data Analysis Using the SAS System
Publisher: SAS Institute
Author(s): Maura E. Stokes

Statisticians and researchers will find Maura Stokes, Charles Davis, and Gary Koch's Categorical Data Analysis Using the SAS System, Second Edition, to be a useful discussion of categorical data analysis techniques as well as an invaluable aid in applying these methods with SAS. Practical examples from a broad range of applications illustrate the use of the FREQ, LOGISTIC, GENMOD, and CATMOD procedures in a variety of analyses. Other procedures discussed include the PHREG and NPAR1WAY procedures. Topics discussed include assessing association in contingency tables and sets of tables, logistic regression and conditional logistic regression, weighted least squares modeling, repeated measurements analyses, log-linear models, and bioassay analysis. The second edition has been revised for use with SAS 8. New topics include additional exact tests, generalized estimating equations, use of the CLASS statement in the LOGISTIC procedure, exact logistic regression using the LOGISTIC procedure, and comparisons of the use of subject-specific models versus population-averaged models.

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     Data Mining for Business Intelligence: Concepts, Techniques, and Applications in Microsoft Office Excel with XLMiner
Publisher: Wiley
Author(s): Galit Shmueli, Nitin R. Patel, Peter C. Bruce

Data Mining for Business Intelligence, Second Edition uses real data and actual cases to illustrate the applicability of data mining (DM) intelligence in the development of successful business models. Featuring complimentary access to XLMiner, the Microsoft Office Excel add-in, this book allows readers to follow along and implement algorithms at their own speed, with a minimal learning curve. In addition, students and practitioners of DM techniques are presented with hands-on, business-oriented applications. An abundant amount of exercises and examples, now doubled in number in the second edition, are provided to motivate learning and understanding. This book helps readers understand the beneficial relationship that can be established between DM and smart business practices, and is an excellent learning tool for creating valuable strategies and making wiser business decisions. New topics include detailed coverage of visualization (enhanced by Spotfire subroutines) and time series forecasting, among a host of other subject matter.

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     Cisco Unified Computing System (UCS) (Data Center): A Complete Reference Guide to the Cisco Data Center Virtualization Server Architecture (Networking Technology)
Publisher: Cisco Press
Author(s): Silvano Gai, Tommi Salli, Roger Andersson

The definitive guide to UCS and the Cisco Data Center Server: planning, architecture, components, deployment, and benefits

With its new Unified Computing System (UCS) family of products, Cisco has introduced a fundamentally new vision for data center computing: one that reduces ownership cost, improves agility, and radically simplifies management. In this book, three Cisco insiders thoroughly explain UCS, and offer practical insights for IT professionals and decision-makers who are evaluating or implementing it.

The authors establish the context for UCS by discussing the implications of virtualization, unified I/O, large memories and other key technologies, and showing how trends like cloud computing and green IT will drive the next-generation data center. Next, they take a closer look at the evolution of server CPU, memory, and I/O subsystems, covering advances such as the Intel XEON 5500, 5600, 7500, DDR3 memory, and unified I/O over 10 Gbps Ethernet.

Building on these fundamentals, the authors then discuss UCS in detail, showing how it systematically overcomes key limitations of current data center environments. They review UCS features, components, and architecture, and demonstrate how it can improve data center performance, reliability, simplicity, flexibility, and energy efficiency. Along the way, they offer realistic planning, installation, and migration guidance: everything decision-makers and technical implementers need to gain maximum value from UCS?now, and for years to come.

Silvano Gai has spent 11 years as Cisco Fellow, architecting Catalyst, MDS, and Nexus switches. He has written several books on networking, written multiple Internet Drafts and RFCs, and is responsible for 80 patents and applications. He teaches a course on this book?s topics at Stanford University.

Tommi Salli, Cisco Technical Marketing Engineer, has nearly 20 years of experience with servers and applications at Cisco, Sun, VERITAS, and Nuova Systems.

Roger Andersson, Cisco Manager, Technical Marketing, spent more than 12 years in the CLARiiON Engineering Division at EMC, and 5 years as Technical Product Manager at VERITAS/Symantec. He is now focused on Cisco UCS system management.

  • Streamline data centers with UCS to systematically reduce cost of ownership
  • Eliminate unnecessary server components?and their setup, management, power, cooling, and cabling
  • Use UCS to scale service delivery, simplify service movement, and improve agility
  • Review the latest advances in processor, memory, I/O, and virtualization architectures for data center servers
  • Understand the specific technical advantages of UCS
  • Integrate UCS 6100 Fabric Interconnect, Cisco UCS 2100 Series Fabric Extenders, UCS 5100 Series Blade Server Enclosures, UCS B-Series Blade Servers, UCS C-Series Rack Servers, and UCS Adapters
  • Use Cisco UCS Manager to manage all Cisco UCS components as a single, seamless entity
  • Integrate third-party management tools from companies like BMC, CA, EMC, IBM, Microsoft, and VMware
  • Practice all this with a copy of Cisco Unified Computing System? Platform Emulator Lite (UCSPE Lite) on the DVD in the back of the book

This book is part of the Networking Technology Series from Cisco Press�, which offers networking professionals valuable information for constructing efficient networks, understanding new technologies, and building successful careers.



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     High Performance Linux Clusters with OSCAR, Rocks, OpenMosix, and MPI (Nutshell Handbooks)
Publisher: O'Reilly Media
Author(s): Joseph D Sloan

To the outside world, a "supercomputer" appears to be a single system. In fact, it's a cluster of computers that share a local area network and have the ability to work together on a single problem as a team. Many businesses used to consider supercomputing beyond the reach of their budgets, but new Linux applications have made high-performance clusters more affordable than ever. These days, the promise of low-cost supercomputing is one of the main reasons many businesses choose Linux over other operating systems.

This new guide covers everything a newcomer to clustering will need to plan, build, and deploy a high-performance Linux cluster. The book focuses on clustering for high-performance computation, although much of its information also applies to clustering for high-availability (failover and disaster recovery). The book discusses the key tools you'll need to get started, including good practices to use while exploring the tools and growing a system. You'll learn about planning, hardware choices, bulk installation of Linux on multiple systems, and other basic considerations. Then, you'll learn about software options that can save you hours--or even weeks--of deployment time.

Since a wide variety of options exist in each area of clustering software, the author discusses the pros and cons of the major free software projects and chooses those that are most likely to be helpful to new cluster administrators and programmers. A few of the projects introduced in the book include:

  • MPI, the most popular programming library for clusters. This book offers simple but realistic introductory examples along with some pointers for advanced use.
  • OSCAR and Rocks, two comprehensive installation and administrative systems
  • openMosix (a convenient tool for distributing jobs), Linux kernel extensions that migrate processes transparently for load balancing
  • PVFS, one of the parallel filesystems that make clustering I/O easier
  • C3, a set of commands for administering multiple systems
Ganglia, OpenPBS, and cloning tools (Kickstart, SIS and G4U) are also covered. The book looks at cluster installation packages (OSCAR & Rocks) and then considers the core packages individually for greater depth or for folks wishing to do a custom installation. Guidelines for debugging, profiling, performance tuning, and managing jobs from multiple users round out this immensely useful book.


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     Programming Collective Intelligence: Building Smart Web 2.0 Applications
Publisher: O'Reilly Media
Author(s): Toby Segaran

Want to tap the power behind search rankings, product recommendations, social bookmarking, and online matchmaking? This fascinating book demonstrates how you can build Web 2.0 applications to mine the enormous amount of data created by people on the Internet. With the sophisticated algorithms in this book, you can write smart programs to access interesting datasets from other web sites, collect data from users of your own applications, and analyze and understand the data once you've found it. Programming Collective Intelligence takes you into the world of machine learning and statistics, and explains how to draw conclusions about user experience, marketing, personal tastes, and human behavior in general--all from information that you and others collect every day. Each algorithm is described clearly and concisely with code that can immediately be used on your web site, blog, Wiki, or specialized application. This book explains:
  • Collaborative filtering techniques that enable online retailers to recommend products or media
  • Methods of clustering to detect groups of similar items in a large dataset
  • Search engine features--crawlers, indexers, query engines, and the PageRank algorithm
  • Optimization algorithms that search millions of possible solutions to a problem and choose the best one
  • Bayesian filtering, used in spam filters for classifying documents based on word types and other features
  • Using decision trees not only to make predictions, but to model the way decisions are made
  • Predicting numerical values rather than classifications to build price models
  • Support vector machines to match people in online dating sites
  • Non-negative matrix factorization to find the independent features in adataset
  • Evolving intelligence for problem solving--how a computer develops its skill by improving its own code the more it plays a game�
Each chapter includes exercises for extending the algorithms to make them more powerful. Go beyond simple database-backed applications and put the wealth of Internet data to work for you.

"Bravo! I cannot think of a better way for a developer to first learn these algorithms and methods, nor can I think of a better way for me (an old AI dog) to reinvigorate my knowledge of the details."
-- Dan Russell, Google

"Toby's book does a great job of breaking down the complex subject matter of machine-learning algorithms into practical, easy-to-understand examples that can be directly applied to analysis of social interaction across the Web today. If I had this book two years ago, it would have saved precious time going down some fruitless paths."
-- Tim Wolters, CTO, Collective Intellect

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     Analyzing Qualitative Data: Systematic Approaches
Publisher: Sage Publications, Inc
Author(s): H. Russell Bernard, Gery W. Ryan

CourseSmart

Congratulations to H. Russell Bernard, who was recently elected as a member of the National Academy of Sciences

?This book does what few others even attempt-to survey a wide range of systematic analytic approaches. I commend the authors for both their inclusiveness and their depth of treatment of various tasks and approaches.? -Judith Preissle, University of Georgia�

?I appreciate the unpretentious tone of the book. The authors provide very clear instructions and examples of many different ways to collect and analyze qualitative data and make it clear that there is no one correct way to do it.? -Cheryl Winsten-Bartlett, North Central University�

?The analytical methodologies are laid out very well, and I will definitely utilize the book with students regarding detailed information and steps to conduct systematic and rigorous data analysis.? -Dorothy Aguilera, Lewis & Clark College��

This book introduces readers to systematic methods for analyzing qualitative data. Unlike other texts, it covers the extensive range of available methods so that readers become aware of the array of techniques beyond their individual disciplines. Part I is an overview of the basics. Part II comprises 11 chapters, each treating a different method for analyzing text. Real examples from the literature across the health and social sciences provide invaluable applied understanding.



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     Data Analysis and Classification: Proceedings of the 6th Conference of the Classification and Data Analysis Group of the Societ� Italiana di ... Data Analysis, and Knowledge Organization)
Publisher: Springer
Author(s):

The volume provides results from the latest methodological developments in data analysis and classification and highlights new emerging subjects within the field. It contains articles about statistical models, classification, cluster analysis, multidimensional scaling, multivariate analysis, latent variables, knowledge extraction from temporal data, financial and economic applications, and missing values. Papers cover both theoretical and empirical aspects.

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