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 columns
to the input table containing the prediction for each row.
*You can use nodes like the linear regression, polynomial regression and
the logistic regression node to create regression models.
Dialog Options
- Append columns with predicted probabilities
-
This has only an effect for target columns with nominal data.
The number of appended columns is equal to the number of categories
of the target column. They represent the probability that a row in
the input data falls in a specific category.
Ports
Input Ports
0 |
The regression model |
1 |
Table for prediction. Missing values will give missing values in the output. |
Output Ports
0 |
Table from input with an additional prediction column. |
This node is contained in KNIME Base Nodes
provided by KNIME GmbH, Konstanz, Germany.