Pipelines

Machine learning pipelines are series of transformers that execute on adata frame. They allow us to combine our feature transformationstogether with our actual predictive algorithms. Pipelines can be assimple as a single transformer or quite complex, involving hundreds offeature transformers and multiple predictive algorithms.

Simple Pipeline Example

The diagram below shows a very simple pipeline that can be serialized to a bundle and then scored using MLeap Runtime. The ideas is that MLeap enables serialization and execution of transformers that operate on continuous and categorical features. A more complicated version of this pipeline may include dimension reduction transformers like PCA and feature selection tranformers like the Chi-Squared selector.

Advanced Pipelines

To see more advanced pipelines, please take a look at our MLeap demo notebooks.