The ML.PRINCIPAL_COMPONENT_INFO function

This document describes the ML.PRINCIPAL_COMPONENT_INFO function, which lets you see the statistics of the principal components in a principal component analysis (PCA) model, such as eigenvalue and explained variance ratio.

Syntax

ML.PRINCIPAL_COMPONENT_INFO(MODEL `project_id.dataset.model`)

Arguments

ML.PRINCIPAL_COMPONENT_INFO takes the following arguments:

Output

ML.PRINCIPAL_COMPONENT_INFO returns the following columns:

Example

The following example retrieves the eigenvalue-related information of each principal component in the model mydataset.mymodel in your default project.

SELECT
  *
FROM
  ML.PRINCIPAL_COMPONENT_INFO(MODEL `mydataset.mymodel`)

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