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Drift Detection by Measuring Distribution Differences

  • Samuel Ackerman,
  • Guy Barash,
  • Eitan Farchi,
  • Orna Raz,
  • Onn Shehory

摘要

This chapter discusses the concepts of populations and samples of observational units and the idea of drift detection as being an inference that drift has occurred in a population distribution based on an observed data sample. It introduces one- and two-sample hypothesis tests for both the univariate and multivariate settings and numeric and categorical data. It discusses issues in the use of significance measures such as p-values and effect sizes.