API Reference#

Welcome to the capymoa API reference. This documentation is automatically generated from the source code and provides detailed information on the classes and functions available in capymoa.

If you are looking to just use CapyMOA, you should start with the tutorials.

Types#

These module provide interfaces for learners, and other basic types used by capymoa.

`capymoa.base`
`capymoa.type_alias`
`capymoa.instance`

Data Streams#

These modules provide classes for loading, and simulating data streams. It also includes utilities for simulating concept drifts.

`capymoa.datasets`	CapyMOA comes with some datasets 'out of the box'.
`capymoa.stream`

Problem Settings#

These modules provide classes for defining machine learning problem settings.

`capymoa.classifier`
`capymoa.regressor`
`capymoa.anomaly`
`capymoa.ssl`
`capymoa.ocl`	Learners and base classes for Online Continual Learning.
`capymoa.drift`
`capymoa.clusterers`
`capymoa.automl`

Evaluation#

These modules provide classes for evaluating learners.

`capymoa.evaluation`
`capymoa.prediction_interval`

Miscellaneous#

These modules provide miscellaneous utilities.

`capymoa.splitcriteria`	Module containing split criteria for decision trees.
`capymoa.misc`
`capymoa.env`	CapyMOA supports a few environment variables that can be used to customize its behavior.

Functions#

Machine learning library tailored for data streams.

capymoa.about()[source]#

Print useful debug information about the CapyMOA setup.

>>> import capymoa
>>> capymoa.about() 
CapyMOA ...