TY - GEN
T1 - Optimal Bayesian Classification When the Training Observations are Serially Dependent
AU - Zollanvari, Amin
AU - Dougherty, Edward R.
PY - 2018/11/16
Y1 - 2018/11/16
N2 - In this study, we construct the optimal Bayesian classifier (OBC) when the training observations are serially dependent. To model the effect of dependency, we assume the training observations are generated from VAR(p), which is a multi-dimensional vector autoregressive process of order p.
AB - In this study, we construct the optimal Bayesian classifier (OBC) when the training observations are serially dependent. To model the effect of dependency, we assume the training observations are generated from VAR(p), which is a multi-dimensional vector autoregressive process of order p.
KW - Optimal Bayesian Classification
KW - Vector Autoregressive Processes
UR - http://www.scopus.com/inward/record.url?scp=85059479867&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85059479867&partnerID=8YFLogxK
U2 - 10.1109/NYSDS.2018.8538943
DO - 10.1109/NYSDS.2018.8538943
M3 - Conference contribution
AN - SCOPUS:85059479867
T3 - 2018 New York Scientific Data Summit, NYSDS 2018 - Proceedings
BT - 2018 New York Scientific Data Summit, NYSDS 2018 - Proceedings
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2018 New York Scientific Data Summit, NYSDS 2018
Y2 - 6 August 2018 through 8 August 2018
ER -