Enhanced machine learning library tailored for data streams, featuring a Python API integrated with MOA backend support. This unique combination empowers users to leverage a wide array of existing algorithms efficiently while fostering the development of new methodologies in both Python and Java.
Hi @heymarco, great work with the experimental version of the pipelines. I have expanded the jupyter notebook. We will continue working on this, but for now it is looking great, thanks again!
This PR contains the first version of pipelines in Capymoa. Most importantly, it contains the classes
Pipeline
andTransformer
.Transformer
s serve as elements in a pipeline and can be used to perform data preprocessing, such as normalization, feature transformation etc.Pipeline
s chain multiple trainsformers and a learner (classifier/regressor). Pipelines themselves serve as classifiers or regressors.This version does not yet support changes in an instance's schema, e.g., due to feature selection. However, we will add this feature in the future.