MLDev: Data Science Experiment Automation and Reproducibility Software

In this paper, we explore the challenges of automating experiments in data science. We propose an extensible experiment model as a foundation for integration of different open source tools for running research experiments. We implement our approach in a prototype open source MLDev software package a...

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Bibliographic Details
Published inData Analytics and Management in Data Intensive Domains Vol. 1620; pp. 3 - 18
Main Authors Khritankov, Anton, Pershin, Nikita, Ukhov, Nikita, Ukhov, Artem
Format Book Chapter
LanguageEnglish
Published Switzerland Springer International Publishing AG 2022
Springer International Publishing
SeriesCommunications in Computer and Information Science
Subjects
Data science
Experiment automation
Reproducibility
Online AccessGet full text
ISBN9783031122842
3031122844
ISSN1865-0929
1865-0937
DOI10.1007/978-3-031-12285-9_1

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Summary:In this paper, we explore the challenges of automating experiments in data science. We propose an extensible experiment model as a foundation for integration of different open source tools for running research experiments. We implement our approach in a prototype open source MLDev software package and evaluate it in a series of experiments yielding promising results. Comparison with other state-of-the-art tools signifies novelty of our approach.
ISBN:9783031122842
3031122844
ISSN:1865-0929
1865-0937
DOI:10.1007/978-3-031-12285-9_1