1.1 - 8.10 - Distribution Matching (ML Engine) - Teradata Vantage

Teradata Vantage™ - Machine Learning Engine Analytic Function Reference

Product
Teradata Vantage
Release Number
1.1
8.10
Release Date
October 2019
Content Type
Programming Reference
Publication ID
B700-4003-079K
Language
English (United States)

Given sample data and reference distributions, the function tests the hypothesis that the sample data comes from the distributions (Hypothesis-Test Mode (ML Engine)). Given the test results, the function finds the distribution that best matches the sample data (Best-Match Mode (ML Engine)).

The Distribution Matching function is composed of the functions DistributionMatchReduce and DistributionMatchMultiInput. DistributionMatchReduce supports these distributions:

  • For continuous variables:
    • Beta
    • Cauchy
    • ChiSq
    • Exponential
    • F
    • Gamma
    • Lognormal
    • Normal
    • T
    • Triangular
    • Uniform
    • Weibull
  • For discrete variables:
    • Binomial
    • Geometric
    • Negative binomial
    • Poisson
    • Uniform

For evaluating the fit of the distribution to the data, the function supports these tests:

  • Anderson-Darling test
  • Kolmogorov-Smirnov test
  • Cramér-von Mises criterion (hypothesis testing only)
  • Pearson’s Chi-squared test