1.1 - 8.10 - PCAScore (ML Engine) - Teradata Vantage

Teradata Vantage™ - Machine Learning Engine Analytic Function Reference

Product
Teradata Vantage
Release Number
1.1
8.10
Published
October 2019
Content Type
Programming Reference
Publication ID
B700-4003-079K
Language
English (United States)

The PCA (ML Engine) function outputs a set of principal components, and each principal component is a linear combination of the set of original predictors.

In the output table, table pca_health_ev_scaled, (from PCA Example) the first-ranked principal component is:

-0.082 * age + 0.387 * bmi + (-0.0935) * bloodpressure + 0.042 * glucose …

Using a similar equation, the PCAScore function uses the coefficients from the output table of the PCA function to compute a principal component score for each observation.

A common use of PCAScore output is principal component regression (PCR).