The Top Ten Algorithms in Data Mining

Editors: Vipin Kumar (U. of Minnesota), Xindong Wu (U. of Vermont)

The Best-Known Algorithms Currently Used in the Data Mining Community
Contributions from recognized leaders in the field

Identifying some of the most influential algorithms that are widely
used in the data mining community, The Top Ten Algorithms in Data
Mining provides a description of each algorithm, discusses its impact,
and reviews current and future research. Thoroughly evaluated by
independent reviewers, each chapter focuses on a particular algorithm
and is written by either the original authors of the algorithm or
world-class researchers who have extensively studied the respective
algorithm.

The book concentrates on the following important algorithms:
C4.5, k-Means, SVM, Apriori, EM, PageRank, AdaBoost, kNN, Naive Bayes,
and CART. Examples illustrate how each algorithm works and highlight
its overall performance in a real-world application. The text covers
key topics - including classification, clustering, statistical
learning, association analysis, and link mining - in data mining
research and development as well as in data mining, machine learning,
and artificial intelligence courses.

By naming the leading algorithms in this field, this book
encourages the use of data mining techniques in a broader realm of
real-world applications. It should inspire more data mining researchers
to further explore the impact and novel research issues of these
algorithms.