Retraction Notice: Analyzing the Performance of Online Adaptive Clustering for Time Series with Head-Based Aggregation
Ankita Agarwal, Murli Manohar Gour, M. P. Karthikeyan · 2024
This paper presents an analytical examine the present day, an internet adaptive clustering technique for time collection statistics with Head-primarily based Aggregation (HBA). Using a Markov chain technique, the authors analyze the asymptotic overall performance of cutting-edge global clustering blunders, which consist of the sum of present-day misclassification and the clustering structure errors. They offer a closed-shape expression new to the predicted global error rate and show its conduct quantitatively beneath distinct eventualities. Thru massive experiments on both synthetic and actual datasets, they show the effectiveness of the proposed method compared to the conventional okay-approach clustering and a few online clustering algorithms. The effects show that the proposed method can successfully seize time collection clustering shape.