A Drift Detection Method Based on Diversity Measure and McDiarmid’s Inequality in Data Streams

2020/01/01 by Yuan Xia, Xia Yuan, Yunlong Zhao · 1 citation
Computer Science · #Anomaly Detection Techniques and Applications #Computer science #Data Stream Mining Techniques #Data mining #Data stream mining #Measure (data warehouse) #Network Security and Intrusion Detection #Operating system #STREAMS

paper · doi:10.1007/978-3-030-64243-3_9

crossref issued 2020/01/01 · crossref published 2020/01/01 · crossref published-print 2020/01/01 · openalex publication_date 2020/01/01 · crossref published-online 2020/12/04 · crossref created 2020/12/04 · crossref deposited 2020/12/04 · crossref indexed 2025/03/25 · openalex created_date 2025/10/10 · openalex updated_date 2026/08/04

Citations

• How good is the Electricity benchmark for evaluating concept drift adaptation
• Comparative accuracies of artificial neural networks and discriminant analysis in predicting forest cover types from cartographic variables

Cited by

• Concept drift [wikipedia]