Using eXpertise2Go: Examining the final conclusions
 
Explanation of eXpertise2Go Conclusions

Minimum confidence factor for accepting a value as a fact: 80.0%
Value 1 of the recommended action is refuel the car with 91.6% confidence

Determined the recommended action is refuel the car with 91.6% confidence from:
  [1]Rule 2 (out of gas) is true and assigned the value refuel the car with 91.6% confidence:
 If the gas tank is empty
Then the recommended action is refuel the car
Determined the gas tank is empty with 91.6% confidence from:
  [1]empty was input with 70.0% confidence [2]Rule 5 (empty tank) is true and assigned the value empty with 72.0% confidence:
 If the result of trying the starter is the car cranks normally
and a gas smell is not present when trying the starter

Then the gas tank is empty with 90% confidence
Determined the result of trying the starter is the car cranks normally with 100.0% confidence from:
  [1]the car cranks normally was input with 100.0% confidence
Determined a gas smell is not present when trying the starter with 80.0% confidence from:
  [1]not present when trying the starter was input with 80.0% confidence
Multi-source confidence calculation for the gas tank is empty: 70.0% + 72.0% of (100% - 70.0%) = 91.6%
All of the values of all of the goals for a consultation are listed first. In this example, there is only one value of one goal: the recommended action. Then, a detailed explanation of the logic eXpertise2Go used to derive each value is provided. A vertical gray bar ties together all of the evidence used to determine the value provided at the top of the bar. This evidence could include rules, user input and default settings.

If multiple sources were combined to determine an attribute's value, the confidence factor (CF) calculations are summarized as the last item beside the gray bar that delineates all of the evidence. The Inference Methods and Uncertainty tutorial explains the techniques used to calculate confidence factors when values are determined from multiple sources and when the if part of a rule is evaluated with some degree of uncertainty.

 
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