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 Clustering for Data Mining: A Data Recovery Approach Often considered more as an art than a science, the field of clustering has been dominated by learning through examples and by techniques chosen almost through trial-and-error. Even the most popular clustering methods--K-Means for partitioning the data set and Ward's method for hierarchical clustering--have lacked the theoretical attention that would establish a firm relationship between the two methods and relevant interpretation aids. Rather than the traditional set of ad hoc techniques, Clustering for Data Mining: A Data Recovery Approach presents a theory that not only closes gaps in K-Means and Ward methods, but also extends them into areas of current interest, such as clustering mixed scale data and incomplete clustering. The author suggests original methods for both cluster finding and cluster description, addresses related topics such as principal component analysis, contingency measures, and data visualization.
 Disaster Recovery Planning: Preparing for the Unthinkable by Jon Toigo, The #1 guide to protecting and recovering your key digital assets--now fully updated.Disaster recovery strategies after 9/11Up-to-the-minute coverage: DR analysis, planning, strategy, testing, and emergency decision-makingSolutions for centralized and decentralized environments, network and end-user recoveryAdvanced storage technologies and "time to data" metricsImplications of Web services and next-generation outsourcingNow more than ever, crucial information for every IT manager, sysadmin, and consultant! "Disaster Recovery Planning, Third Edition" is a start-to-finish update to the #1 guide to disaster recovery planning and implementation. Thoroughly revised to reflect the latest strategies and technologies, it also presents the disaster recovery lessons taught by 9/11, the California energy crisis, and the anthrax scare. In this book, Toigo offers focused, hands-on blueprints for disaster recovery in every environment, centralized and decentralized--with detailed coverage of building DR systems that address networks and encompass end-users who still maintain crucial enterprise data on local PCs and notebooks.
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