1.1 - 8.10 - CCM Output - 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)

Output Table Schema

Column Data Type Description
cause VARCHAR Input attribute (column) being evaluated as potential causal variable.
effect VARCHAR Input attribute (column) being evaluated as potential effect variable.
library_size INTEGER Size of library evaluated.
correlation DOUBLE PRECISION For numerical cause variables: correlation between values predicted by effect attribute and true value of cause attribute.

For categorical cause variables: NULL

jaccard_index DOUBLE PRECISION For categorical cause variables: Jaccard similarity index between values predicted by effect attribute and true value of cause attribute.

For numerical cause variables: NULL

lower_bound DOUBLE PRECISION Lower bound of 95% confidence interval of prediction contained in correlation or jaccard_index column (whichever is not NULL).
upper_bound DOUBLE PRECISION Upper bound of the 95% confidence interval of prediction contained in correlation or jaccard_index column (whichever is not NULL).
effect_size DOUBLE PRECISION Depends on library_size:
library_size effect_size
Smallest library size used with each cause/effect pair Estimated effect size of increasing library size from smallest to largest value.

For a numerical effect: Cohen's q statistic.

For a categorical effect: difference between two similarity measures.

Other library sizes NULL

An effect_size greater than approximately 0.25 indicates a causal relationship.

effect_size_sd DOUBLE PRECISION Standard deviation of effect size.
embedding_dimension INTEGER [Column appears only with multiple dimensions.] Number of past values to use when predicting given value of time series.