Workflow

This page provides a short example workflow in Jupyter Notebooks. It is designed such that the main steps, features, assumptions, and outcomes of CoPro become clear.

As model input data, the data set downloadable from Zenodo was used.

Even though the model can be perfectly executed using notebooks, the main (and more convenient) way of model execution is the command line script (see Runner script).

An interactive version of the content shown here can be accessed via Binder.

• 1. Model initialization and selection procedure
• 2. Obtaining samples matrix and target values
• 3. Initializing and executing the machine-learning model
• 4. Projecting conflict risk

3. Settings 1. Model initialization and selection procedure