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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, and includes nearly 60 computational examples covering all stages of clustering, from data pre-processing to cluster validation and results interpretation.
This author's unique attention to data recovery methods, theory-based advice, pre- and post-processing issues that are beyond the scope of most texts, and clear, practical instructions for real-world data mining make this book ideally suited for virtually all purposes: for teaching, for self-study, and for professional reference. |
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Computer Security HandbookThe definitive formula for computer security, from power outages to theft and sabotage
Whether you are in charge of many computers, or even one important one, there are immediate steps you can take to safeguard your company’s computer system and its contents. The Computer Security Handbook provides a readable and... | | Arithmetic Optimization Techniques for Hardware and Software Design
Obtain better system performance, lower energy consumption, and avoid hand-coding arithmetic functions with this concise guide to automated optimization techniques for hardware and software design. High-level compiler optimizations and high-speed architectures for implementing FIR filters are covered, which can improve performance in... | | Microsoft .NET Compact Framework Kick Start Microsoft .NET Compact Framework Kick Start is the fastest path to mastering the Microsoft.NET Compact Framework-Microsoft's next generation development framework for creating complex applications for the Pocket PC and Windows CE platforms. Using it, you can leverage your knowledge of C#... |
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