|Sometimes the knowledge in rules is not certain. Rules then may be enhanced by adding information about how certain the conclusions drawn from the rules may be. Our aim in this secion is to describe certainty factors and their manipulation.|
|Keywords: certainty factor|
if the infection is primary-bacteremia and the site of the culture is one of the sterile sites and the suspected portal of entry is the gastrointestinal tract then there is suggestive evidence (0.7) that the infection is bacteroid
Certainty factors have been quantified using various different systems, including linguistics ones (certain, fairly certain, likely, unlikely, highly unlikely, definitely not) and various numeric scales, such as 0-10, 0-1, and -1 to 1. We shall concentrate on the -1 to 1 version.
Certainty factors may apply both to facts and to rules, or rather to the conclusion(s) of rules.
Assume CF(P1) = 0.6, CF(P2) = 0.4, CF(P3) = 0.2
CF(P1 and P2) = min(0.6, 0.4) = 0.4
CF(0.4, P3) = max(0.4, 0.2) = 0.4
CF(C1) = 0.7 * 0.4 = 0.28
CF(C2) = 0.3 * 0.4 = 0.12
CFR1(C) + CFR2(C) - CFR1(C) * CFR2(C)
| when CFR1(C)|
are both positive
CFR1(C) + CFR2(C) + CFR1(C) * CFR2(C)
are both negative
[CFR1(C) + CFR2(C)]/[1 - min(|CFR1(C)|, |CFR2(C)|)]
are of opposite sign
|Summary: Uncertain Reasoning|
|Certainty factors quantify the confidence that an expert might have in a conclusion that s/he has arrived at. We have given rules for combining certainty factors to obtain estimates of the certainty to be associated with conclusions obtained by using uncertain rules and uncertain evidence.|
|Exercises on uncertain reasoning [- try them before clicking ...] Solutions to exercises|
CRICOS Provider Code No. 00098G
Copyright (C) Bill Wilson, 2002, except where another source is acknowledged. Much of the material on this page is based on an earlier version by Claude Sammut.