Accelerating prototype selection with spatial abstraction

arXiv:2403.11020v1 Announce Type: new
Abstract: The increasing digitalization in industry and society leads to a growing abundance of data available to be processed and exploited. However, the high volume of data requires considerable computational resources for applying machine learning approaches. Prototype selection techniques have been applied to reduce the requirements of computational resources that are needed by these techniques. In this paper, we propose an approach for speeding up existing prototype selection techniques. It builds an abstract representation of the …

abstract abstraction arxiv computational cs.lg data digitalization however industry leads machine machine learning reduce requirements resources society spatial type