Novel Architecture Enhances Regression in Data Streams with Outlier Detection and Drift Adaptation

This research from ArXiv presents a dual-channel architecture aimed at improving data stream regression performance. The work focuses on outlier detection and concept drift adaptation, which are crucial for real-time applications.

• •Proposes a dual-channel architecture for improved data stream regression.
• •Addresses the challenges of outlier detection in streaming data.
• •Aims to achieve low-latency concept drift adaptation.