# Multi-Label Classification

Multi-label classification models predict multiple outcomes. In Aporia, these models are represented with the `multi-label` model type.

Examples of multi-label classification problems:

* Is this song sad, happy, funny, rock, jazz, or all simultaneously?
* Does this movie belong to one or more of the 'romantic', 'comedy', 'documentary', 'thriller' categories, or all simultaneously?

### Data Format In DB

If you have a model with multi category prediction, then your database may look like the following:

<table><thead><tr><th width="76">id</th><th width="132">feature1 (numeric)</th><th width="119">feature2 (boolean)</th><th width="163">prediction (array)</th><th width="155">label (array)</th><th width="191">timestamp (datetime)</th></tr></thead><tbody><tr><td>1</td><td>13.5</td><td>True</td><td>[Action, Horror]</td><td>[Drama, Horror]</td><td>2014-10-19 10:23:54</td></tr><tr><td>2</td><td>-8</td><td>False</td><td>[Drama, Horror]</td><td>[Thriller]</td><td>2014-10-19 10:24:24</td></tr></tbody></table>

To integrate this type of model follow our [Quickstart](https://docs.aporia.com/introduction/quickstart), and during the schema mapping remember to include a `array`prediction field and `array`actual field and linked them together.

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