Binary

Context

• The Binary algorithm produces the desired value through interpolation, as in Fuzzy Logic.
• Among the three available methods, it generates distributions that have the lowest Entropy.
• Using the Binary algorithm for generating a Target Mean/Value would be appropriate if two conditions are met:
  • There is no uncertainty regarding the evidence, i.e. we want the evidence to represent a specific numerical value. “No uncertainty” would typically apply in situations in which we want to simulate the effects of nodes that represent variables under our control.
  • The desired numerical value is not directly available by setting Hard Evidence. In fact, a distribution produced by the Binary algorithm would coincide with Hard Evidence  if the requested Target Value/Mean precisely matched the value of a particular state.

Usage

If we select Binary, the Target Mean/Value is generated by interpolating between values of two adjacent states, hence the name. Here, a “mix” of the values of two states, i.e., JNJ<=−0.009 and JNJ<=−0.002, produces the desired mean of −0.01.