Gathering meta-data from public repositories

• Grant number: 23/03958-2
• Support Opportunities: Scholarships in Brazil - Scientific Initiation
• Effective date (Start): April 01, 2023
• Effective date (End): June 30, 2024
• Field of knowledge: Physical Sciences and Mathematics - Computer Science
• Principal Investigator: Ana Carolina Lorena
• Grantee: Nathan Falcão Carvalho
• Host Institution: Divisão de Ciência da Computação (IEC). Instituto Tecnológico de Aeronáutica (ITA). Ministério da Defesa (Brasil). São José dos Campos , SP, Brazil
• Associated research grant: 21/06870-3 - Beyond algorithm selection: meta-learning for data and algorithm analysis and understanding, AP.JP2
• Associated scholarship(s): 23/11801-6 - Improving public dataset characterization using OpenML, BE.EP.IC

Abstract

The OpenML repository is widely employed by the Machine Learning (ML) community, storing a large number of datasets along with the results of computational experiments run on the same data. The objective of this work is to generate a meta-dataset in the attribute-value format joining the characteristics of the OpenML datasets and also the performance achieved by different ML techniques in their solution, in order to support meta-learning tasks. For such, the Python API associated with the repository will be explored and used.