OMEGA: Optimizing Machine Learning by Evaluating Generated Algorithms
For ML researchers, OMEGA offers an end-to-end framework for automated algorithm discovery, though the novelty is incremental as it combines existing techniques.
OMEGA automates AI research by generating novel ML classifiers from idea to executable code, producing algorithms that outperform scikit-learn baselines across 20 benchmark datasets.
In order to automate AI research we introduce a full, end-to-end framework, OMEGA: Optimizing Machine learning by Evaluating Generated Algorithms, that starts at idea generation and ends with executable code. Our system combines structured meta-prompt engineering with executable code generation to create new ML classifiers. The OMEGA framework has been utilized to generate several novel algorithms that outperform scikit-learn baselines across a robust selection of 20 benchmark datasets (infinity-bench). You can access models discussed in this paper and more in the python package: pip install omega-models.