Rule.compatibility: Return the compatibility degrees of a rule with all instances...
In SIMIDAT/SDEFSR: Subgroup Discovery Algorithms for R

Description Usage Arguments Value

The rules passed to this functions MUST have a vector representation in CANONICA form. This function was made for being used mainly for the FuGePSD algorithm.

1 2	Rule.compatibility(example, rule_cat, rule_num, catParticip, numParticip, xmin, xmedio, xmax, n_matrices, max_cat, max_num, t_norm)

`example`	The instances of the dataset, a matrix with one example PER COLUMN and without the CLASS ATTRIBUTE.
`rule_cat`	Part of the rule with the categorical values.
`rule_num`	Part of the rule with the numerical values.
`catParticip`	vector indicating which categorical attributes participate in the rule and so, they must be evaluated.
`numParticip`	vector indicating which numerical attributes participate in the rule and so, they must be evaluated.
`xmin`	numeric vector which indicate the minimum value of the fuzzy sets of every numeric attribute that participate in the rule.
`xmedio`	numeric vector which indicate the medium value of the fuzzy sets of every numeric attribute that participate in the rule.
`xmax`	numeric vector which indicate the maximum value of the fuzzy sets of every numeric attribute that participate in the rule.
`n_matrices`	number of fuzzy sets that there are in the rule (The length of vectors xmin, xmedio and xmax)
`max_cat`	numeric vector indicating the maximum value of categorical values.
`max_num`	numeric vector indicating the maximum value for fuzzy partitions on every attribute
`t_norm`	The T-norm to use to compute the compatibility degree. 0 for minimum t-norm. Other value for product t-norm