PCA Apply

This node applies a projection to the principal components on the given input data. The data model of the PCA computation node can be applied to arbitrary data to reduce it to a given number of dimensions.
The information preservation rates in the selection of the target dimensions give the expected approximation rates based on the training data fed into the connected PCA Compute node. These rates assume that data fed into the predictor is equally distributed as the data the PCA was computed for initially.

Input ports

1. Type: Transformation
   Transformation model
   The Model used to reduce the data's dimensionality.
2. Type: Table
   Table to transform
   The data whose dimensionality shall be reduced.

Output ports

1. Type: Table
   Transformed data
   The original data (if not excluded) plus columns for the projected dimensions.