# Multiple Linear Regression

**URL:** <https://forum.knime.com/t/multiple-linear-regression/10701>\
**Category:** KNIME Analytics Platform\
**Created:** [April 8, 2018, 7:19pm UTC](https://forum.knime.com/t/multiple-linear-regression/10701 "2018-04-08T19:19:00Z")\
**Posts on this page:** 1\
**Showing post:** 2

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**Author:** ![ScottF](https://forum-cdn.knime.com/user_avatar/forum.knime.com/scottf/32/61316_2.png) [@ScottF](https://forum.knime.com/u/ScottF)\
**Post date:** [April 9, 2018, 2:36pm UTC](https://forum.knime.com/t/multiple-linear-regression/10701/2 "2018-04-09T14:36:26Z")

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Hi @GK1724 -

You’ll want to use the **Linear Regression Learner** node, along with the **Regression Predictor** node. Here’s a very simple example using the Iris dataset, predicting petal width based on the other available variables. The Learner node is where you find the model coefficients and associated p-values, and the Predictor node contains the predictions for the test set. The **Numeric Scorer** node outputs some simple summary statistics (R^2, RMSE, etc).

 ![2018-04-09%2009_31_53-KNIME%20Analytics%20Platform](https://forum-cdn.knime.com/uploads/default/original/1X/b12a6442cb82ac6e94b70b5e0da0913bbad472bd.png)

[IrisLinearRegressionExample.knwf](https://forum-cdn.knime.com/uploads/default/original/1X/75044a07eee66a832be210dfd2362b129ba5fc6d.knwf) (18.7 KB)

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