R: Unsupervised identification of a capacity from profiles
entropy.capa.ident
R Documentation
Unsupervised identification of a capacity from profiles
Description
This function estimates a capacity using as argument a set
of data under the form: datum=(score on attribute 1, ..., score on attribute
n). The approach roughly consists in replacing the subjective notion
of importance of a subset of attributes by that of
information content of a subset of attributes, which is estimated
from the data by means of a parametric entropy measure. For
more details, see the references hereafter.
An object of class data.frame containing the
discretized data. Each column of the data.frame must
be a factor. Each line corresponds to a datum.
entropy
An object of class character containg the name
of the parametric entropy measure to be used for the estimation. The
allowed values are "renyi" and "havrda.charvat".
parameter
An object of class numeric containing he value
of the parameter of the choosen entropy. The parameter value must be
a positive real number. If equal to 1, the Shannon entropy is used.
Value
Returns an object of class capacity.
References
I. Kojadinovic (2004), Estimation of the weights of interacting
criteria from the set of profiles by means of information-theoretic
functionals, European Journal of Operational Research 155:3, pages 741-751.
I. Kojadinovic (2005), Unusupervised aggregation of commensurate
correlated attributes by means of the Choquet integral and entropy
functionals, International Journal of Intelligent Systems, in press.
## a set of randomly generated data
## for instance, marks on a [0,20] scale
p <- data.frame(matrix(runif(500,0,20),100,5))
names(p) <- c("Stat","Prob","Alg","Cal","Eng")
## discretization
p[p <= 5] <- 1
p[p > 5 & p <= 10] <- 2
p[p > 10 & p <= 15] <- 3
p[p > 15] <- 4
d <- data.frame(factor(p[[1]]),
factor(p[[2]]),
factor(p[[3]]),
factor(p[[4]]),
factor(p[[5]]))
## associated unsupervised capacity
mu <- entropy.capa.ident(d)
mu