A Model-Based Approach to Experiment-Driven Evolution of ML Workflows

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216208%3A11320%2F25%3A10508014" target="_blank" >RIV/00216208:11320/25:10508014 - isvavai.cz</a>

Result on the web

<a href="https://doi.org/10.5220/0013380500003896" target="_blank" >https://doi.org/10.5220/0013380500003896</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.5220/0013380500003896" target="_blank" >10.5220/0013380500003896</a>

Result language

angličtina

Original language name

A Model-Based Approach to Experiment-Driven Evolution of ML Workflows

Original language description

Machine Learning (ML) has advanced significantly, yet the development of ML workflows still relies heavily on expert intuition, limiting standardization. MLOps integrates ML workflows for reliability, while AutoML automates tasks like hyperparameter tuning. However, these approaches often overlook the iterative and experimental nature of the development of ML workflows. Within the ongoing ExtremeXP project (Horizon Europe), we propose an experiment-driven approach where systematic experimentation becomes central to ML workflow evolution. The framework created within the project supports transparent, reproducible, and adaptive experimentation through a formal metamodel and related domain-specific language. Key principles include traceable experiments for transparency, empowered decision-making for data scientists, and adaptive evolution through continuous feedback. In this paper, we present the framework from the model-based approach perspective. We discuss the lessons learned from the use of the metamodel-centric approach within the project-especially with use-case partners without prior modeling expertise.

Czech name

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Czech description

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Type

D - Article in proceedings

CEP classification

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OECD FORD branch

10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Project

—

Continuities

S - Specificky vyzkum na vysokych skolach

Publication year

2025

Confidentiality

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Article name in the collection

International Conference on Model Driven Engineering and Software Development

ISBN

978-989-758-729-0

ISSN

2184-4348

e-ISSN

2184-4348

Number of pages

9

Pages from-to

354-362

Publisher name

scitepress

Place of publication

Neuveden

Event location

Porto, Portugal

Event date

Feb 26, 2025

Type of event by nationality

WRD - Celosvětová akce

UT code for WoS article

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