An effective cost-sensitive sparse online learning framework for imbalanced streaming data classification and its application to online anomaly detection

MLA

Zhong Chen, et al. “An Effective Cost-Sensitive Sparse Online Learning Framework for Imbalanced Streaming Data Classification and Its Application to Online Anomaly Detection.” Knowledge and Information Systems, vol. 65, Sept. 2022, pp. 59–87. EBSCOhost, https://doi.org/10.1007/s10115-022-01745-x.

APA

Zhong Chen, Victor Sheng, Andrea Edwards, & Kun Zhang. (2022). An effective cost-sensitive sparse online learning framework for imbalanced streaming data classification and its application to online anomaly detection. Knowledge and Information Systems, 65, 59–87. https://doi.org/10.1007/s10115-022-01745-x

Chicago

Zhong Chen, Victor Sheng, Andrea Edwards, and Kun Zhang. 2022. “An Effective Cost-Sensitive Sparse Online Learning Framework for Imbalanced Streaming Data Classification and Its Application to Online Anomaly Detection.” Knowledge and Information Systems 65 (September): 59–87. doi:10.1007/s10115-022-01745-x.