Validating fuzzy logic values
In the same way, you shouldn't consider a forecast experiment to be complete until you find out whether the forecast was successful. The three most important reasons to verify forecasts are: There are many types of forecasts, each of which calls for slightly different methods of verification. The table below lists one way of distinguishing forecasts, along with verification methods that are appropriate for that type of forecast. David Stephenson has proposed a classification scheme for forecasts. Murphy, 1986: The attributes diagram: A geometrical framework for assessing the quality of probability forecasts. If we take the term forecast to mean a prediction of the future state (of the weather, stock market prices, or whatever), then forecast verification is the process of assessing the quality of a forecast. Ziehmann, 2003: A note on the use of the word 'likelihood' in statistics and meteorology.
The examples are all drawn from the meteorological world (since the people creating this web site are themselves meteorologists or work with meteorologists), but the verification methods can easily be applied in other fields. Types of forecasts and verification What makes a forecast good? Gives examples for each method, with links and references for further information.