# GAMA: a General Automated Machine learning Assistant

arXiv: https://arxiv.org/abs/2007.04911 · HTML: https://mlsanity.com/paper/2007.04911/

## Key facts

- Cited by 15 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 9 Jul 2020.

## Built on by (most cited first, 15 of 15)

- [AMLB: an AutoML Benchmark](https://mlsanity.com/paper/2207.12560/) (2022)
- [Position: A Call to Action for a Human-Centered AutoML Paradigm](https://mlsanity.com/paper/2406.03348/) (2024)
- [AutoM3L: An Automated Multimodal Machine Learning Framework with Large Language Models](https://mlsanity.com/paper/2408.00665/) (2024)
- [Online AutoML: An adaptive AutoML framework for online learning](https://mlsanity.com/paper/2201.09750/) (2022)
- [Don't Waste Your Time: Early Stopping Cross-Validation](https://mlsanity.com/paper/2405.03389/) (2024)
- [Meta-Learning for Unsupervised Outlier Detection with Optimal Transport](https://mlsanity.com/paper/2211.00372/) (2022)
- [AutoMLBench: A Comprehensive Experimental Evaluation of Automated Machine Learning Frameworks](https://mlsanity.com/paper/2204.08358/) (2022)
- [Automated Imbalanced Learning](https://mlsanity.com/paper/2211.00376/) (2022)
- [UniAutoML: A Human-Centered Framework for Unified Discriminative and Generative AutoML with Large Language Models](https://mlsanity.com/paper/2410.12841/) (2024)
- [AutoML Benchmark with shorter time constraints and early stopping](https://mlsanity.com/paper/2504.01222/) (2025)
- [CLAMS: A System for Zero-Shot Model Selection for Clustering](https://mlsanity.com/paper/2407.11286/) (2024)
- [Can time series forecasting be automated? A benchmark and analysis](https://mlsanity.com/paper/2407.16445/) (2024)
- [AutoML-Med: A Framework for Automated Machine Learning in Medical Tabular Data](https://mlsanity.com/paper/2508.02625/) (2025)
- [Automated Machine Learning for Unsupervised Tabular Tasks](https://mlsanity.com/paper/2510.07569/) (2025)
- [Large Language Models for Automated Cross-Domain Machine Learning Task Type Identification: A Benchmark Dataset and Evaluation](https://mlsanity.com/paper/2609.35335/) (2026)

## Abstract (arXiv)

The General Automated Machine learning Assistant (GAMA) is a modular AutoML system developed to empower users to track and control how AutoML algorithms search for optimal machine learning pipelines, and facilitate AutoML research itself. In contrast to current, often black-box systems, GAMA allows users to plug in different AutoML and post-processing techniques, logs and visualizes the search process, and supports easy benchmarking. It currently features three AutoML search algorithms, two model post-processing steps, and is designed to allow for more components to be added.