rbcoverage | R Documentation |
This function computes rule base coverage, i.e. a an average of maximum membership degree at which each row of data fires the rules in rule base.
rbcoverage( x, rules, tnorm = c("goedel", "goguen", "lukasiewicz"), onlyAnte = TRUE )
x |
Data for the rules to be evaluated on. Could be either a numeric matrix or numeric vector. If matrix is given then the rules are evaluated on rows. Each value of the vector or column of the matrix represents a predicate - it's numeric value represents the truth values (values in the interval [0, 1]). |
rules |
Either an object of class "farules" or list of character
vectors where each vector is a rule with consequent being the first element
of the vector. Elements of the vectors (predicate names) must correspond to
the |
tnorm |
A character string representing a triangular norm to be used
(either |
onlyAnte |
TRUE if only antecedent-part of a rule should be evaluated. Antecedent-part of a rule are all predicates in rule vector starting from the 2nd position. (First element of a rule is the consequent - see above.) If FALSE, then the whole rule will be evaluated (antecedent part together with consequent). |
Let f_{ij} be a truth value of i-th rule on j-th row of
data x
. Then m_j = max(f_{.j}) is a maximum truth value that
is reached for the j-th data row with the rule base. Then the rule
base coverage is a mean of that truth values, i.e. rbcoverage =
mean(m_.).
A numeric value of the rule base coverage of given data.
Michal Burda
M. Burda, M. Štěpnička, Reduction of Fuzzy Rule Bases Driven by the Coverage of Training Data, in: Proc. 16th World Congress of the International Fuzzy Systems Association and 9th Conference of the European Society for Fuzzy Logic and Technology (IFSA-EUSFLAT 2015), Advances in Intelligent Systems Research, Atlantic Press, Gijon, 2015.
fire()
, reduce()
x <- matrix(1:20 / 20, nrow=2) colnames(x) <- letters[1:10] rules <- list(c('a', 'c', 'e'), c('b'), c('d', 'a'), c('c', 'a', 'b')) rbcoverage(x, rules, "goguen", TRUE) # returns 1 rules <- list(c('d', 'a'), c('c', 'a', 'b')) rbcoverage(x, rules, "goguen", TRUE) # returns 0.075)
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