Output - Aster Analytics

Teradata AsterĀ® Analytics Foundation User GuideUpdate 2

Product
Aster Analytics
Release Number
7.00.02
Published
September 2017
Language
English (United States)
Last Update
2018-04-17
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B700-1022
lifecycle
previous
Product Category
Software
CCM Output Schema
Column Name Data Type Description
cause VARCHAR Input attribute (column) being evaluated as a potential causal variable.
effect VARCHAR Input attribute (column) being evaluated as a potential effect variable.
library_size INTEGER Size of the library evaluated.
correlation DOUBLE PRECISION For numerical cause variables: correlation between the values predicted by the effect attribute and the true value of the cause attribute.

For categorical cause variables: NULL

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

For numerical cause variables: NULL

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

For other library sizes: NULL

For a numerical effect: Cohen's q statistic.

For a categorical effect: difference between the two similarity measures.

An effect_size greater than approximately 0.25 indicates a causal relationship.

effect_size_sd DOUBLE PRECISION Standard deviation of the effect size.