# Polynomial Regression¶

Educational widget that interactively shows regression line for different regressors.

## Signals¶

**Inputs**:

**Data**

Input data set. It needs at least two continuous attributes.

**Preprocessor**

Data preprocessors.

**Learner**

Regression algorithm used in the widget. Default set to Linear Regression.

**Outputs**:

**Learner**

Regression algorithm used in the widget.

**Predictor**

Trained regressor.

**Coefficients**

Regressor coefficients if it has them.

## Description¶

This widget interactively shows regression line using any of the regressors from *Orange3 Regression* module.
In the widget, polynomial expansion can be set.
Polynomial expansion is a regulation of the degree of polynom that is used to transform the input data and has an effect
on the shape of a curve. If polynomial expansion is set to 1 it means that untransformed data are used in the regression.

Regressor name.

*Input*: independent variable on axis x.*Polynomial expansion*: degree of polynomial expansion.*Target*: dependent variable on axis y.*Save Image*saves the image to the computer in a .svg or .png format.*Report*includes widget parameters and visualization in the report.

## Example¶

We loaded *iris* data set with the **File** widget.
Then we connected **Linear Regression** learner to the **Polynomial Regression** widget.
In the widget we selected *petal length* as our *Input* variable and *petal width* as our *Target* variable.
We set *Polynomial expansion* to 1 which gives us a linear regression line. The result is shown on the figure below.

The line can fit better if we increase the **Polynomial expansion** parameter. Say, we set it to 3.

To observe different results, change **Linear Regression** to any other regression learner from Orange. Example below is done with **Regression Tree** learner.