Understanding Polynomial Regression

Understanding Polynomial Regression

This Article expands on Simple Linear Regression and Multiple Linear Regression, ensure you have a good understanding of these two topic areas before continuing

This Article expands on [Simple Linear Regression_](https://medium.com/ai-in-plain-english/linear-regression-in-python-part-1-simple-linear-regression-fae7672ff552) and [Multiple Linear Regression_](https://medium.com/ai-in-plain-english/understanding-multiple-linear-regression-2672c955ec1c), ensure you have a good understanding of these two topic areas before continuing.

What is Polynomial Regression?

Polynomial Regression is used to capture non-linear relationships between variables.

For example:

Image for post

For linear relationships we use Linear Regression.


Take a look at the following graph looking at the Humidity and Pressure *values in *Svged, Hungary[ Yes i like Weather data :) ]

Image for post

  • We can see there is a trend in the data, which is *non-linear *so we use Polynomial Regression

  • The job of Polynomial regression is to find a suitable relationship between Humidity and Pressure, such as the following:

    Image for post

  • We can then use the model produced by polynomial regression to make suitable predictions for Humidity given any Pressure value.

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