This GitHub repository contains code and resources related to the research project on Selectivity Estimation for Spatial Filters using Optimizer Feedback from a Machine Learning perspective. The project focuses on leveraging optimizer feedback to improve the estimation of selectivity for multi-dimensional spatial predicates. Various Machine Learning models, including neural networks, tree-based models, and instance-based models, are explored to address this challenging task efficiently. The repository also includes datasets and some learned models used in the study.
The work in this repository is licensed under the MIT License. Please refer to the LICENSE file for more details.
- Nadir GUERMOUDI (LRIT/ University of Tlemcen)
- Houcine MATALLAH (LRIT/ University of Tlemcen)
- Amin MESMOUDI (LIAS/University of Poitiers)
- Seif-Eddine BENKABOU (LIAS/University of Poitiers)
- Allel HADJALI (LIAS/ISAE-ENSMA)