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Applied Data Mining: Statistical Methods for Business and Industry |
| Paolo Giudici (University of Pavia, Italy) |
| The increasing availability of data in the current information society has led to the need for valid tools for its modelling and analysis. Data mining and applied statistical methods are the appropriate tools to extract knowledge from such data. Applied Data Mining: Statistical Methods for Business and Industry provides an accessible introduction to data mining methods in a consistent and application-oriented statistical framework. It describes six case studies, taken from real industry projects, highlighting the current applications of data mining methods. *Provides an introduction to data mining methods and applications. *Includes coverage of classical and Bayesian multivariate statistical methodology as well as of machine learning and computational data mining methods.
*Includes many recent developments, such as association and sequence rules, graphical Markov models, memory-based reasoning, credit risk and web mining.
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