Description
Usage
Arguments
Details
Value
Author(s)
See Also
Examples
View source: R/perceive.R
Examine rules in a list and remove all of them for whose other more specific
rules are present in the list. The specificity is determined by calling the
is.specific()
function. This operation is a part of the
pbld()
inference mechanism.
 (
rules,
,
= ("global", "local"),
fired = ,
= ,
=
)

rules 
A list of character vectors where each element is a fuzzy set
name (a predicate) and thus each such vector forms a rule.

fsets 
A valid instance of the fsets() class such that all predicates
in rules (i.e., all values of all character vectors in rules$rules )
can be found in colnames(fsets)

type 
The type of perception to use. It can be either "local"
or "global" (default).

fired 
If type=="global" then this argument can be NULL. If
type is "local" then fired must be a numeric vector of
values in the interval [0,1] indicating the truth values of all rules,
i.e. the length of the vector must be equal to the number of rules in the
rules argument.

vars 
A deprecated parameter that must be NULL . Formerly, it was
a named (typically character) vector that determined which
predicates originate from the same variable, i.e. which of them semantically
deal with the same property. For that purpose, each value from any vector
stored in the rules list must be present in names(vars) . See
also vars() function of the fsets() class.

specs 
A deprecated parameter that must be NULL . Formerly, it was
a square numeric matrix containing values from \{0, 1\}.
It is a specificity matrix for which each row and column corresponds to an
rules 'es predicate specs[i][j] = 1 if and only if the
ith predicate is more specific (i.e. the corresponding fuzzy set is a
subset of) than the jth predicate (i.e. x[, j] ). See also
specs() function of the fsets() class.

In other words, for each rule x
in the rules
list, it searches for another
rule y
such that is.specific(y, x)
returns TRUE. If yes then
x
is removed from the list.
A modified list of rules for which no other more specific rule
exists. (Each rule is a vector.)
Michal Burda
is.specific()
, fsets()
, fcut()
, lcut()
 # prepare fsets
f < ((a=0:1, b=0:1, =0:1, d=0:1))
# run perceive function: (sm.a, bi.c) has
# more specific rule (ve.sm.a, bi.c)
((('sm.a', 'bi.c'),
('ve.sm.a', 'bi.c'),
('sm.b', 'sm.d')),
f)

beerda/lfl documentation built on Oct. 17, 2020, 8:57 p.m.