Work

Comparative Analysis of Automated Machine Learning Libraries: Pycaret, H2o, Tpot, Auto-sklearn, and Flaml

Year: 2024

Type: article

Abstract: Automated Machine Learning (AutoML) frameworks have gained significant popularity in recent years, making machine learning accessible to a broader audience by automating many of the tasks traditionally performed by data scientists and domain experts. This paper presents a comparative analysis of five prominent AutoML libraries: PyCaret, H2O.ai, TPOT, Auto-sklearn, and FLAML. Each of these libraries provides automated solutions for model selection, hyperparameter tuning, and other machine learning tasks. The goal of this study is to assess their performance, ease of use, flexibility, and suitability for various types of machine learning problems. The comparison is based on multiple factors, including ease of use, performance, customization, resource efficiency, and suitability. This research aims to help researchers, practitioners, and developers in selecting the most appropriate AutoML library based on their specific needs and resources. Keywords: AutoML, PyCaret, H2O.ai, TPOT, Auto-sklearn, FLAML

Source: INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT

DOI: 10.55041/ijsrem39119

Authors: Dr. Parashuram S. Vadar, Dr. Tejashree T. Moharekar, Dr. Urmila R. Pol

Institution: Shivaji University

Language: English

Topic: Machine Learning and Data Classification

Subfield: Artificial Intelligence

Field: Computer Science

Domain: Physical Sciences

Open Access status: bronze

OpenAlex ID: W4404756276

FWCI: 0.456

Cites:

Cited by: 3

Related to: 10