CCM Output - Teradata Vantage

Machine Learning Engine Analytic Function Reference

Product
Teradata Vantage
Release Number
9.02
9.01
2.0
1.3
Published
February 2022
Language
English (United States)
Last Update
2022-02-10
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B700-4003
lifecycle
previous
Product Category
Teradata Vantageā„¢

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.