A similarity matrix of samples was generated by treating each age class as an individual variable.
If α is a wff and a is an individual variable, then (∀a)α is a wff.
The limitations of local sensitivity methods have been highlighted and it has been shown that CCA provides a measure of both an individual variable's contribution and the effectiveness of the parameter set as a whole.
This can be done as follows: A term is first defined as either (1) an individual variable or (2) an individual constant or (3) any expression formed by prefixing a function variable or function constant of degree n to any n terms (these terms the arguments of the function symbol are usually separated by commas and enclosed in parentheses).
The formation rules for well-formed formulas are the obvious ones; in particular universal and existential quantification is allowed for any variable, be it an individual variable, a predicate variable, or a function variable.
For instance, a predicative function of an individual variable must have order 1 (in current terminology, it is elementarily definable and quantifies only over individuals).
For the task of modality fusion the following random variables are defined: (a) variable CL j, which corresponds to the semantic class e j with which the particular BN structure is associated, and (b) variables A j, C j and M j, where an individual variable is introduced for every considered modality.
An expression $t$ is a term if, and only if, (i) $t$ is an individual variable, or (ii) $t$ is an individual constant, or (iii) $t$ is an expression of the form $f^{n}_{i}t_{1}, \ldots, t_{n}$, where $f^{n}_{i}$ an $n$-place function symbol and $t_1$, …, $t_n $are themselves terms.
Sensory 'constitution' could be an individual variable associated with and helping to form personality characteristics.
To measure the importance of an individual variable (compound), Gini indexes are compared for a tree containing the variable to a tree obtained by permuting the variable.
