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Books > Computing & IT > Applications of computing > Databases > Data mining
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Pattern Recognition - A Quality of Data Perspective (Hardcover)
Loot Price: R3,135
Discovery Miles 31 350
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Pattern Recognition - A Quality of Data Perspective (Hardcover)
Expected to ship within 12 - 19 working days
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A new approach to the issue of data quality in pattern recognition
Detailing foundational concepts before introducing more complex
methodologies and algorithms, this book is a self-contained manual
for advanced data analysis and data mining. Top-down organization
presents detailed applications only after methodological issues
have been mastered, and step-by-step instructions help ensure
successful implementation of new processes. By positioning data
quality as a factor to be dealt with rather than overcome, the
framework provided serves as a valuable, versatile tool in the
analysis arsenal. For decades, practical need has inspired intense
theoretical and applied research into pattern recognition for
numerous and diverse applications. Throughout, the limiting factor
and perpetual problem has been data--its sheer diversity,
abundance, and variable quality presents the central challenge to
pattern recognition innovation. Pattern Recognition: A Quality of
Data Perspective repositions that challenge from a hurdle to a
given, and presents a new framework for comprehensive data analysis
that is designed specifically to accommodate problem data. Designed
as both a practical manual and a discussion about the most useful
elements of pattern recognition innovation, this book: Details
fundamental pattern recognition concepts, including feature space
construction, classifiers, rejection, and evaluation Provides a
systematic examination of the concepts, design methodology, and
algorithms involved in pattern recognition Includes numerous
experiments, detailed schemes, and more advanced problems that
reinforce complex concepts Acts as a self-contained primer toward
advanced solutions, with detailed background and step-by-step
processes Introduces the concept of granules and provides a
framework for granular computing Pattern recognition plays a
pivotal role in data analysis and data mining, fields which are
themselves being applied in an expanding sphere of utility. By
facing the data quality issue head-on, this book provides students,
practitioners, and researchers with a clear way forward amidst the
ever-expanding data supply.
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