A feature value may be unknown. A score should expect an unknown value of a feature, and still produce a score value. In such a case, the score has to produce a result taking into account some amount of uncertainty. The same applies to a rating.
To let a user know about how accurate a score value is, a score provides a confidence level for the calculated score value.
Let’s define a confidence level as a float number in the interval
0 means the lowest confidence, and
10 means the highest confidence.
Both a score and a rating provide a confidence level for score and rating values that they produce. The confidence level mainly depends on a number of unknown feature values that were used to calculate a score or rating value.
The way how a confidence level is calculated may depend on a particular score. A score should also take into account the weights of the sub-scores during calculating a score value.