Regression Predictor

Predicts the response using a regression model. The node needs to be connected to a regression node model* and some test data. It is only executable if the test data contains the columns that are used by the learner model. This node appends a new column to the input table containing the prediction for each row. *You can use the Linear Regression Learner node or the Polynomial Regression Learner node to create regression models.

Input ports

1. Type: PMML
   Regression model
   The regression model
2. Type: Table
   Data for prediction
   Table for prediction. Missing values will give missing values in the output.

Output ports

1. Type: Table
   Predicted data
   Table from input with an additional prediction column.