Statistical Learning & Data Mining

PUBLISHED


Viewing: 1 - 10 of 37
Published:
April 04, 2013
Editor(s):
Ting Yu; Nitesh Chawla; Simeon Simoff
Going beyond performing simple analyses, researchers involved in the highly dynamic field of computational intelligent data analysis design algorithms that solve increasingly complex data problems in changing environments, including economic, environmental, and social data. Computational 
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Published:
March 26, 2013
Author(s):
David Roi Hardoon; Galit Shmueli
Assuming no prior knowledge or technical skills, Getting Started with Business Analytics: Insightful Decision-Making explores the contents, capabilities, and applications of business analytics. It bridges the worlds of business and statistics and describes business analytics from a non-commercial 
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Published:
December 17, 2012
Author(s):
Naiyang Deng; Yingjie Tian; Chunhua Zhang
Support Vector Machines: Optimization Based Theory, Algorithms, and Extensions presents an accessible treatment of the two main components of support vector machines (SVMs)—classification problems and regression problems. The book emphasizes the close connection between optimization theory and SVMs 
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Published:
October 17, 2012
Author(s):
Boris Mirkin
Often considered more of an art than a science, books on clustering have been dominated by learning through example with techniques chosen almost through trial and error. Even the two most popular, and most related, clustering methods—K-Means for partitioning and Ward's method for hierarchical 
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Published:
September 07, 2012
Editor(s):
Guozhu Dong; James Bailey
A Fruitful Field for Researching Data Mining Methodology and for Solving Real-Life ProblemsContrast Data Mining: Concepts, Algorithms, and Applications collects recent results from this specialized area of data mining that have previously been scattered in the literature, making them more 
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Published:
June 06, 2012
Author(s):
Zhi-Hua Zhou
An up-to-date, self-contained introduction to a state-of-the-art machine learning approach, Ensemble Methods: Foundations and Algorithms shows how these accurate methods are used in real-world tasks. It gives you the necessary groundwork to carry out further research in this evolving field. After 
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$79.95
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Published:
February 15, 2012
Author(s):
James Wu; Stephen Coggeshall
Drawing on the authors’ two decades of experience in applied modeling and data mining, Foundations of Predictive Analytics presents the fundamental background required for analyzing data and building models for many practical applications, such as consumer behavior modeling, risk and marketing 
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Published:
December 20, 2011
Editor(s):
Yunqian Ma; Yun Fu
Trained to extract actionable information from large volumes of high-dimensional data, engineers and scientists often have trouble isolating meaningful low-dimensional structures hidden in their high-dimensional observations. Manifold learning, a groundbreaking technique designed to tackle these 
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Published:
December 20, 2011
Editor(s):
Marcia J. Bates
In order to be effective for their users, information retrieval (IR) systems should be adapted to the specific needs of particular environments. The huge and growing array of types of information retrieval systems in use today is on display in Understanding Information Retrieval Systems: Management 
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Published:
December 19, 2011
Editor(s):
Mireille Gettler Summa; Leon Bottou; Bernard Goldfarb; Fionn Murtagh; Catherine Pardoux; Myriam Touati
Data analysis is changing fast. Driven by a vast range of application domains and affordable tools, machine learning has become mainstream. Unsupervised data analysis, including cluster analysis, factor analysis, and low dimensionality mapping methods continually being updated, have reached new 
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$93.95
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