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.
Views
- 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.
Workflows
- No workflows found
Links
- No links available
Developers
You want to see the source code for this node? Click the following button and we’ll use our super-powers to find it for you.