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Linear Algebra Tools For Data Mining

RRP $554.99

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This comprehensive volume presents the foundations of linear algebra ideas and techniques applied to data mining and related fields. Linear algebra has gained increasing importance in data mining and pattern recognition, as shown by the many current data mining publications, and has a strong impact in other disciplines like psychology, chemistry, and biology. The basic material is accompanied by more than 550 exercises and supplements, many accompanied with complete solutions and MATLAB applications.


History Of Gold Mining In The United States

RRP $16.99

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Gold was known by the Indians to exist in the United States long before the white people discovered it, but unlike the Indians of Mexico, the more northern natives did not make elaborate use of it, and it did not seriously attract the attention of the settlers until shortly before the beginning of the nineteenth century. No very important mining, however, was done until after 1800, when a little gold began to be obtained in North Carolina. Long before that time the gold of California had also been known to the natives and to the Franciscan monks, but that country then belonged to Mexico and was not taken by the United States until 1846...


Data Mining

RRP $271.99

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This comprehensive textbook on data mining details the unique steps of the knowledge discovery process that prescribe the sequence in which data mining projects should be performed. Data Mining offers an authoritative treatment of all development phases from problem and data understanding through data preprocessing to deployment of the results. This knowledge discovery approach is what distinguishes this book from other texts in the area. It concentrates on data preparation, clustering and association rule learning (required for processing unsupervised data), decision trees, rule induction algorithms, neural networks, and many other data mining methods, focusing predominantly on those which have proven successful in data mining projects.

Based upon the authors' previous successful book on data mining and knowledge discovery, this new volume has been extensively expanded, making it an effective instructional tool for advanced-level undergraduate and graduate courses. This book offers:

  • A suite of exercises at the end of every chapter, designed to enhance the reader's understanding of the theory and proficiency with the tools presented

  • Links to all-inclusive instructional presentations for each chapter to ensure easy use in classroom teaching

  • Extensive appendices covering relevant mathematical material for convenient look-up

  • Methods for addressing issues related to data privacy and security within the context of data mining, enabling the reader to balance potentially conflicting aims

  • Summaries and bibliographical notes for each chapter, providing a broader perspective of the concepts and methods described

Researchers, practitioners and students are certain to consider this volume an indispensable resource in successfully accomplishing the goals of their data mining projects.



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