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Linear Regression Learner

DeprecatedKNIME Base Nodes version 4.3.3.v202105242122 by KNIME AG, Zurich, Switzerland

Performs a multivariate linear regression. Select in the dialog a target column (combo box on top), i.e. the response. The two lists in the center of the dialog allow you to include only certain (numeric) columns which represent the (independent) variables. Make sure the columns you want to have included being in the right "include" list. The checkbox at the bottom controls whether or not the error on the training data should be computed. The error value is then available in the view. Calculating the error requires performing one extra scan on the data.
Additionally, specify the rows that shall be available in the view. Specify the first row number and the total count.
If the optional PMML inport is connected and contains preprocessing operations in the TransformationDictionary those are added to the learned model.

Input Ports

Table on which to perform regression.
Optional PMML port object containing preprocessing operations.

Output Ports

Model to connect to a predictor node.


Linear Regression Result View
Displays statistics and the parameters of the resulting hyperplane.
Linear Regression Scatterplot View
Displays the input data along with the regression line in a scatterplot. The y-coordinate is fixed to the response column (the column that has been approximated) while the x-column can be chosen in the view. Note: If you have multiple input variables, this view is only an approximation. It will fix the value of each variable that is not shown in the view to its mean. Thus, this view generally only makes sense if you only have a few input variables.

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