Clustering Progress - Teradata Warehouse Miner

Teradata® Warehouse Miner™ User Guide - Volume 3Analytic Functions

Product
Teradata Warehouse Miner
Release Number
5.4.6
Published
November 2018
Language
English (United States)
Last Update
2018-12-07
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B035-2302
Product Category
Software
  • Iteration — This represents the number of the step in the Expectation Maximization clustering algorithm as it seeks to converge on a solution maximizing the log likelihood function.
  • Log Likelihood — This is the log likelihood value calculated at the end of this step in the Expectation Maximization clustering algorithm. It does not appear when the K-Means option is used.
  • Diff — This is simply the difference in the log likelihood value between this and the previous step in the modeling process, starting with 0 at the end of the first step. It does not appear when the K-Means option is used.
  • Timestamp — This is the day, date, hour, minute and second marking the end of this step in processing.