Mlf-core: a framework for deterministic machine learning.

ABSTRACT:

Motivation

Machine learning has shown extensive growth in recent years and is now routinely applied to sensitive areas. To allow appropriate verification of predictive models before deployment, models must be deterministic. Solely fixing all random seeds is not sufficient for deterministic machine learning, as major machine learning libraries default to the usage of nondeterministic algorithms based on atomic operations.

Results

Various machine learning libraries released deterministic counterparts to the nondeterministic algorithms. We evaluated the effect of these algorithms on determinism and runtime. Based on these results, we formulated a set of requirements for deterministic machine learning and developed a new software solution, the mlf-core ecosystem, which aids mach

SUBMITTER: Heumos L 

PROVIDER: S-EPMC10089676 | biostudies-literature | 2023 Apr

REPOSITORIES: biostudies-literature