著者・編者edited by Mireille Gettler Summa ... [et al.]
一般注記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
関連情報Series in computer science and data analysis
掲載誌Series in computer science and data analysis
連携機関・データベース国立情報学研究所 : CiNii Research
NACSIS書誌ID（NCID）https://ci.nii.ac.jp/ncid/BB08886415 : BB08886415