Clustering Progress - Teradata Warehouse Miner

• 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.