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Data Mining: The Textbook

Users: 1 - Average Rating: 5.00

The book discusses fundamental learning methods, data types and their applications. The main aim of the authors is to make students understand the connections
between different problems and data types by providing suitable scenarios and comparing different methods.
The book mainly focuses on clustering and classification problems, association pattern mining, outlier analysis and comprehensively discusses the vast diversity of methods used by the data mining community in the context of these problems. The textbook assumes a basic knowledge of probability, statistics, and linear algebra, stronger mathematical background, while it is helpful for the more advanced chapters, it is not a prerequisite.


Data Analytics, Machine Learning

Target Group:


Cite as:
Aggarwal, C. C., Data mining: the textbook, Springer, 2015.

Author of the review:
Giulia Cademartori
University of Genoa


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