Statistical learning and data science

Author(s)

• Summa, Mireille Gettler

Bibliographic Information

Statistical learning and data science

edited by Mireille Gettler Summa ... [et al.]

（Series in computer science and data analysis）

CRC Press, c2012

• : hardback

Note

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

Details

• NCID: BB08886415
• ISBN:
  • 9781439867631
• LCCN: 2011036558
• Country Code: us
• Title Language Code: eng
• Text Language Code: eng
• Place of Publication: Boca Raton
• Pages/Volumes: xv, 227 p.
• Size: 27 cm
• Classification:
  • LCC : Q325.5
  • DC23 : 006.3/1
  • NDLC : MA121
• Subject Headings:
  • LCSH : Machine learning -- Statistical methods
  • LCSH : Data mining
  • FREE : BUSINESS & ECONOMICS / Statistics. bisacsh
  • FREE : COMPUTERS / Machine Theory. bisacsh
  • FREE : MATHEMATICS / Probability & Statistics / General. bisacsh
• Parent Bibliography ID:
  • BA64913131