How to implement new methods into pipeline using H2O?

Question

I'm new to machine learning and H2O tools, and I'd like to know if there is a high-level H2O interface that allows us to implement new methods into a pipeline.

I know we can build models thanks to Flow interface and export them as POJO/MOJO. But how can I, for example, decide to use kNN method as an imputation method for my data, when Flow only allows simple imputation like mean/mode ?

Answer 1

You cannot add new methods in your pipeline in Flow. Flow is just a simple GUI which allows you to do things like create train/test splits, train models, test models and view some metrics. You'd have to use the R or Python client to create a pipeline of any sort.