IEEE Systems, Man, and Cybernetics Magazine - January 2018 - 50

good way. There are examples of how
algorithms will scale in space and
time. It is actually, by itself, worth
reading for those clustering or wanting to cluster big data.
In summary, this book provides
all you need to know about basic,
and still widely used, clustering algorithms. It will tell you how to get
features, set up algorithms, and evaluate the results, and it provides an
idea of what algorithm might be best
for your data. The big-data discussion is excellent and helps connect
the basic algorithms to a few of the
many different modifications to im-

prove them. The book is a good reference or textbook on clustering.
About the Author
Lawrence O. Hall (lohall@mail.usf
.edu) earned his B.S. degree in applied
mathematics from Florida Institute of
Technology, Melbourne, in 1980 and
his Ph.D. degree in computer science
from Florida State University, Tallahassee, in 1986. He is a distinguished university professor in the Department of
Computer Science and Engineering at
the University of South Florida (USF),
Tampa. He served as department chair
from 2008 through 2015. In 2012, he

What + If = IEEE

received the Norbert Wiener Award
from the IEEE Systems, Man, and
Cybernetics Society. He was named
the 2017 Theodore and Venette Askounes-Ashford Distinguished Scholar
Award winner at USF. He has authored
or coauthored more than 270 publications in journals, conference papers,
and book chapters. He is a fellow of
the American Association for the
Advancement of Science and the International Association for Pattern Recognition. He is a member of the
National Academy of Inventors and an
IEEE Fellow.

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