choice {relations} | R Documentation |
Choose objects based on an ensemble of relations between these.
relation_choice(x, method = "symdiff", weights = 1, control = list(), ...)
x |
an ensemble of endorelations. |
method |
a character string specifying one of the built-in methods, or a function to be taken as a user-defined method. See Details for available built-in methods. |
weights |
a numeric vector with non-negative case weights.
Recycled to the number of elements in the ensemble given by x
if necessary. |
control |
a list of control parameters. See Details. |
... |
a list of control parameters (overruling those specified
in control ). |
A social choice function is a rule for choosing from a set D of objects, i.e., selecting suitable subsets of D. Voting rules used in elections are the most prominent example of such functions, which typically aggregate individual preferences (e.g., of voters).
Choice methods "symdiff"
and "CKS"
(currently the only
one available) chooses a given number k of objects
(“winners”) by determining a relation R minimizing
sum_b w_b d(R_b, R) over all relations for which winners are
always strictly preferred to losers, without any further constraints
on the relations between pairs of winners or pairs of losers, where
d is symmetric difference (symdiff, “Kemeny-Snell”) or
Cook-Kress-Seiford (CKS) dissimilarity, respectively, the R_b
are crisp endorelations, and w_b is the case weight given to
R_b. (Note that this is different from computing consensus
preference relations.)
Available control options include:
k
all
all
is false, only a
single optimal choice is computed.A set with the chosen objects, or a list of such sets.
data("SVM_Benchmarking_Classification") ## Determine the three best classification learners in the above sense. relation_choice(SVM_Benchmarking_Classification, k = 3)