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Books > Computing & IT > Applications of computing > Artificial intelligence
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Data Analysis in Bi-partial Perspective: Clustering and Beyond (Hardcover, 1st ed. 2020)
Loot Price: R2,873
Discovery Miles 28 730
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Data Analysis in Bi-partial Perspective: Clustering and Beyond (Hardcover, 1st ed. 2020)
Series: Studies in Computational Intelligence, 818
Expected to ship within 10 - 15 working days
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This book presents the bi-partial approach to data analysis, which
is both uniquely general and enables the development of techniques
for many data analysis problems, including related models and
algorithms. It is based on adequate representation of the essential
clustering problem: to group together the similar, and to separate
the dissimilar. This leads to a general objective function and
subsequently to a broad class of concrete implementations. Using
this basis, a suboptimising procedure can be developed, together
with a variety of implementations. This procedure has a striking
affinity with the classical hierarchical merger algorithms, while
also incorporating the stopping rule, based on the objective
function. The approach resolves the cluster number issue, as the
solutions obtained include both the content and the number of
clusters. Further, it is demonstrated how the bi-partial principle
can be effectively applied to a wide variety of problems in data
analysis. The book offers a valuable resource for all data
scientists who wish to broaden their perspective on basic
approaches and essential problems, and to thus find answers to
questions that are often overlooked or have yet to be solved
convincingly. It is also intended for graduate students in the
computer and data sciences, and will complement their knowledge and
skills with fresh insights on problems that are otherwise treated
in the standard "academic" manner.
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