Articles by "Data Mining"

Showing posts with label Data Mining. Show all posts

Ian H. Witten, Eibe Frank, Mark A. Hall, Christopher J. Pal ... 655 pages - Publisher: Morgan Kaufmann; 4th edition (October, 2016) ... Language: English - ASIN: B01MG31RL3 by Amazon ...

Data Mining: Practical Machine Learning Tools and Techniques, Fourth Edition, offers a thorough grounding in machine learning concepts, along with practical advice on applying these tools and techniques in real-world data mining situations. This highly anticipated fourth edition of the most acclaimed work on data mining and machine learning teaches readers everything they need to know to get going, from preparing inputs, interpreting outputs, evaluating results, to the algorithmic methods at the heart of successful data mining approaches. Extensive updates reflect the technical changes and modernizations that have taken place in the field since the last edition, including substantial new chapters on probabilistic methods and on deep learning. Accompanying the book is a new version of the popular WEKA machine learning software from the University of Waikato. Authors Witten, Frank, Hall, and Pal include today's techniques coupled with the methods at the leading edge of contemporary research.

Petros Xanthopoulos, Panos M. Pardalos, Theodore B. Trafalis ... 59 pages - Publisher: Springer New York; (November, 2012) ... Language: English - ASIN: B00AYR26DI by Amazon

Data uncertainty is a concept closely related with most real life applications that involve data collection and interpretation. Examples can be found in data acquired with biomedical instruments or other experimental techniques. Integration of robust optimization in the existing data mining techniques aim to create new algorithms resilient to error and noise.This work encapsulates all the latest applications of robust optimization in data mining. This brief contains an overview of the rapidly growing field of robust data mining research field and presents the most well known machine learning algorithms, their robust counterpart formulations and algorithms for attacking these problems. This brief will appeal to theoreticians and data miners working in this field.

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