Spark PCA

This node performs a principal component analysis (PCA) on the given data using the Apache Spark implementation . The input data is projected from its original feature space into a space of (possibly) lower dimension with a minimum of information loss.

Input ports

1. Type: Spark Data
   Spark DataFrame/RDD
   Input Spark DataFrame/RDD

Output ports

1. Type: Spark Data
   Projected Input DataFrame/RDD
   The input DataFrame/RDD projected onto the principal components. Input columns that were not included in the principal component analysis are retained.
2. Type: Spark Data
   Principal Component Matrix
   A DataFrame/RDD with the principal components matrix.