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Books > Computing & IT > Applications of computing > Databases > Data mining
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Data Clustering in C++ - An Object-Oriented Approach (Hardcover)
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Data Clustering in C++ - An Object-Oriented Approach (Hardcover)
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Data clustering is a highly interdisciplinary field, the goal of
which is to divide a set of objects into homogeneous groups such
that objects in the same group are similar and objects in different
groups are quite distinct. Thousands of theoretical papers and a
number of books on data clustering have been published over the
past 50 years. However, few books exist to teach people how to
implement data clustering algorithms. This book was written for
anyone who wants to implement or improve their data clustering
algorithms. Using object-oriented design and programming
techniques, Data Clustering in C++ exploits the commonalities of
all data clustering algorithms to create a flexible set of reusable
classes that simplifies the implementation of any data clustering
algorithm. Readers can follow the development of the base data
clustering classes and several popular data clustering algorithms.
Additional topics such as data pre-processing, data visualization,
cluster visualization, and cluster interpretation are briefly
covered. This book is divided into three parts-- * Data Clustering
and C++ Preliminaries: A review of basic concepts of data
clustering, the unified modeling language, object-oriented
programming in C++, and design patterns * A C++ Data Clustering
Framework: The development of data clustering base classes * Data
Clustering Algorithms: The implementation of several popular data
clustering algorithms A key to learning a clustering algorithm is
to implement and experiment the clustering algorithm. Complete
listings of classes, examples, unit test cases, and GNU
configuration files are included in the appendices of this book as
well as in the CD-ROM of the book. The only requirements to compile
the code are a modern C++ compiler and the Boost C++ libraries.
General
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