The value for the variable is known, such as the specific state of a discrete node.
No evidence has been set. I.e. the variable's value is unknown/missing/null.
A distribution is used to indicate evidence that is uncertain.
For a discrete variable with a number of possible states, soft evidence implies that we have some information about the configuration of the states, but we are uncertain of the exact state. For example if a node has 3 states and we are sure that the last state is not possible, we can have evidence of the form {1, 1, 0}. We can also assign a distribution such as {0.3,0.4, 0.3}.
See {@link com.bayesserver.inference.IEvidence#setStates(Variable, double[])} for information on how to set this type of evidence.
The variable has evidence at one or more times.
The type of evidence for a variable. When a variable is set to a specific value, this is called {@link com.bayesserver.inference.EvidenceType#Hard Hard} evidence.
For a discrete variable with a number of possible states, soft evidence implies that we have some information about the configuration of the states, but we are uncertain of the exact state. For example if a node has 3 states and we are sure that the last state is not possible, we can have evidence of the form {1, 1, 0}. We can also assign a distribution such as {0.3,0.4, 0.3}.
See {@link com.bayesserver.inference.IEvidence#setStates(Variable, double[])} for information on how to set this type of evidence.