This repository contains experimentation on selectivity estimation when dealing with spatial filters using optimizer feedback. Explore our experiments and methodologies in selectivity estimation for spatial filters.
Framework for spatial selectivity estimation using machine learning and optimizer feedback. Addresses both RCC filters and distance-based filters by transforming estimation into regression task. Compares neural networks, tree-based models and instance-based approaches against traditional RTree and histogram methods across 14 spatial datasets.
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