# Regression

Regression models predict a `numeric` value. In Aporia, these models are represented with the `regression` model type.

Examples of regression problems:

* What will the temperature be in Seattle tomorrow?
* For product X, how many units will sell?
* How many days until this customer stops using the application?
* What price will this house sell for?

### Data Format In DB

Regression predictions are usually represented in a database with a `numeric` column. For example:

<table><thead><tr><th width="93">id</th><th width="116">feature1 (numeric)</th><th width="121">feature2 (boolean)</th><th width="215">predicted_temperature (numeric)</th><th width="190">actual_temperature (numeric)</th><th width="193">timestamp (datetime)</th></tr></thead><tbody><tr><td>1</td><td>13.5</td><td>True</td><td>22.83</td><td>24.12</td><td>2017-01-01 12:00:00</td></tr><tr><td>2</td><td>123</td><td>False</td><td>26.04</td><td>25.99</td><td>2017-01-01 12:01:00</td></tr><tr><td>3</td><td>42</td><td>True</td><td>29.01</td><td>11.12</td><td>2017-01-01 12:02:00</td></tr></tbody></table>

To integrate this type of model follow our [Quickstart](https://docs.aporia.com/introduction/quickstart).

Check out the [data sources section](https://docs.aporia.com/data-sources) for more information about how to connect from different data sources.