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:

idfeature1 (numeric)feature2 (boolean)prediction (array)label (array)timestamp (datetime)




[Action, Horror]

[Drama, Horror]

2014-10-19 10:23:54




[Drama, Horror]


2014-10-19 10:24:24

To integrate this type of model follow our Quickstart, and during the schema mapping remember to include a arrayprediction field and arrayactual field and linked them together.

Check out the data sources section for more information about how to connect from different data sources.

Last updated