Introduction

The Machine Learning Research Wizard (MLWiz) is a framework that you can use to easily train and evaluate machine learning models for tabular, image, timeseries, and graph data.

MLWiz helps you to:

• automatize model selection and risk assessment,

• foster reproducibility and robustness of results,

• reduce the amount of boilerplate code to write,

• make it flexible enough to encompass a wide range of use cases for research.

• support a number of different hardware set ups, including a cluster of nodes (using Ray),

To run an experiment, you usually rely on 2 YAML configuration files:

• one to pre-process the dataset and create the data splits,

• another with information about the experiment itself and the hyper-parameters to try.

MLWiz is a minimal, but extended version of PyDGN (https://github.com/diningphil/PyDGN).

Installation:

Automated tests passing on Linux.

The recommended way to install the library is to follow the steps to install torch and torch_geometric prior to installing MLWiz.

Then simply run

pip install mlwiz