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.


Custom prediction column name
Allows you to specify a customized name for the prediction column that is appended to the input table. If the checkbox is not checked, "Prediction (target)" (where target is the name of the target column of the provided regression model) is used as default.

Input Ports

The regression model
Table for prediction. Missing values will give missing values in the output.

Output Ports

Table from input with an additional prediction column.


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