Forecast CF

After all the evidence is collected, the hypothesis (i.e., the category of the target variable) with the highest CF is forecast. Most often the CF for this hypothesis is treated as MB, while the CF for the opposite hypothesis as MD, and the final CF is the difference between the two. In some cases, however, all the CFs are shown in the forecast. 

The forecast is also accompanied by the odds to give the user some sense how much money we are willing to bet in favor of the forecast category. The odds are calculated as 

O = (100 + CF)/(100 - CF).

The odds may also be adjusted for some subjective reason. The relationship between O and CF is shown in the figure below.

With these odds the user will have equal chances of winning or losing money. Therefore placing a bet, the user is advised to be a bit more conservative and bet, say, 2:1 instead of 3:1.

As shown in the previous sections, CFs are a simple and convenient way to manage the uncertainty in the climate system. Still, there is also some uncertainty (or imprecision) in assignment of CFs to evidence and rules. In practice, however, it turns out that the knowledge content of rules is much more important than the algebra of confidences that holds the system together. 

In conclusion, we would like to underscore that the forecasts we produce are categorical and the CFs reflect our confidence that the forecast category of the target variable will occur. Nevertheless, in many cases (but not always), a high CF also means a high magnitude of the anomaly. This is particularly common for two opposite categories, such as warm-cold or dry-wet. For this and other reasons (short time series, state of our knowledge about the climate system, etc.) we prefer to work with two or three categories of climate variables.