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.
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