Statistical learning and data science

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Bibliographic Information

Title
"Statistical learning and data science"
Statement of Responsibility
edited by Mireille Gettler Summa ... [et al.]
Publisher
  • CRC Press
Publication Year
  • c2012
Book size
27 cm
Series Name / No
  • : hardback

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Notes

Summary: "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 heights of achievement in the incredibly rich data world that we inhabit.Statistical Learning and Data Science is a work of reference in the rapidly evolving context of converging methodologies. It gathers contributions from some of the foundational thinkers in the different fields of data analysis to the major theoretical results in the domain. On the methodological front, the volume includes conformal prediction and frameworks for assessing confidence in outputs, together with attendant risk. It illustrates a wide range of applications, including semantics, credit risk, energy production, genomics, and ecology ... "--Back cover

Includes bibliographical references (p. 205-223) and index

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