Iterative Forgetting: Online Data Stream Regression Using Database-Inspired Adaptive Granulation

arXiv:2403.09588v1 Announce Type: new
Abstract: Many modern systems, such as financial, transportation, and telecommunications systems, are time-sensitive in the sense that they demand low-latency predictions for real-time decision-making. Such systems often have to contend with continuous unbounded data streams as well as concept drift, which are challenging requirements that traditional regression techniques are unable to cater to. There exists a need to create novel data stream regression methods that can handle these scenarios. We present a database-inspired datastream regression model …

abstract arxiv concept continuous cs.db cs.lg data database data stream data streams decision demand drift financial iterative latency low making modern predictions real-time regression requirements sense systems telecommunications transportation type