PCAReduce Output Table Schema
Each row represents a principal component. The rows are in descending order based on the standard deviation, which is a measure of the variation in the data set that was captured by that principal component.
|component_rank||INTEGER||Rank of principal component. Components are ranked in descending order of standard deviation (and variance).|
|dimension_i||DOUBLE PRECISION||[Column appears once for each dimension.] Values of ith dimension of data set.|
|sd||DOUBLE PRECISION||Standard deviation of components in eigenvector represented by row.|
|var_proportion||DOUBLE PRECISION||Proportion of variance of components in eigenvector represented by row.|
|cumulative_var||DOUBLE PRECISION||Cumulative variance of components in eigenvector represented by row.|
|mean||VARCHAR||One row of this column contains a list of average values, one for each target_column_i in the input table. The list has this format:
[average [, average ...]]
The outer brackets appear in the table.
The other rows of this column contain NULL.