TY - GEN
T1 - Sensitivity analysis for threshold decision making with Bayesian belief networks
AU - Van Der Gaag, Linda C.
AU - Coupé, Veerle M.H.
PY - 2000
Y1 - 2000
N2 - The probability assessments of a Bayesian belief network generally include inaccuracies. These inaccuracies influence the reliability of the network's output. An integral part of investigating the output's reliability is to study its robustness. Robustness pertains to the extent to which varying the probability assessments of the network influences the output. It is studied by subjecting the network to a sensitivity analysis. In this paper, we address the issue of robustness of a belief network's output in view of the threshold model for decision making. We present a method for sensitivity analysis that provides for the computation of bounds between which a network's assessments can be varied without inducing a change in recommended decision.
AB - The probability assessments of a Bayesian belief network generally include inaccuracies. These inaccuracies influence the reliability of the network's output. An integral part of investigating the output's reliability is to study its robustness. Robustness pertains to the extent to which varying the probability assessments of the network influences the output. It is studied by subjecting the network to a sensitivity analysis. In this paper, we address the issue of robustness of a belief network's output in view of the threshold model for decision making. We present a method for sensitivity analysis that provides for the computation of bounds between which a network's assessments can be varied without inducing a change in recommended decision.
UR - http://www.scopus.com/inward/record.url?scp=34250370639&partnerID=8YFLogxK
U2 - https://doi.org/10.1007/3-540-46238-4-4
DO - https://doi.org/10.1007/3-540-46238-4-4
M3 - Conference contribution
SN - 3540673504
SN - 9783540673507
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 37
EP - 48
BT - AI*IA 99
T2 - 6th Congress of the Italian Association for Artificial Intelligence, AI*IA 99
Y2 - 14 September 1999 through 17 September 1999
ER -