The **Linear Regression** block enables you to apply a linear regression predictive model to a dataset.

The following demonstrates how to use the **Linear Regression** block to predict the mass of a banana based on the other variables used to describe a banana in the input *bananas.csv* dataset.

- Import the
*bananas.csv*dataset onto a Workflow canvas using the**Text File Import**block. - Expand the
**Model Training**group in the Workflow palette, then click and drag a**Linear Regression**block onto the Workflow canvas. - Click
**Output**port of the*bananas*dataset block and drag a connection towards the**Input**port of the**Linear Regression**block. - Double-click the
**Linear Regression**block to display the**Configure Linear Regression**dialog box. - In the
**Configure Linear Regression**dialog Box:

- In the
**Dependent variable**drop-down list, select**Mass(g)**. - In the
**Unselected Regressors**list, select**Length(cm)**. - Click
**Select**to move the selected variable to the**Selected Regressors**list.

- In the
- Click
**OK**to save the configuration and close the**Configure Linear Regression**dialog box.

A green execution status is displayed in the **Output** ports of the **Linear Regression **block and the new **Linear Regression Model**. The **Linear Regression** block output can be used with a **Score** block to make predictions on a dataset.