Soft Ordinal Embedding (SOE)
Performs SOE for a given part of ordinal informaiton.
SOE(CM, N, p = 2, c = 0.1, maxit = 1000, report = 100, iniX = "rand",rnd=10000)
CM |
A matrix whose rows represent ordinal information:
A row vector (i,j,k,l) means xi_{ij} < xi_{kl}, where xi_{ij} is a dissimilarity
between object i and object j.
If the number of given ordinal comparisons is more than 100000, then SOE randomly chooses |
N |
The number of objects. |
p |
The number of dimensions. |
c |
Scale parameter which only takes strictly positive value. |
maxit |
Maximum number of iteretions. |
report |
The frequency of reports. Defaults to every 100 iterations. |
iniX |
Matrix with starting values for embedding (optional). |
rnd |
The number of ordinal comarisons which are randomly chosen from given ordinal comparisons |
SOE returns a list with components:
X |
The best corrdinate matrix with p columns whose rows give the coordinates of objects. |
str |
The value of the stress function of SOE corresponding to |
Yoshikazu Terada
library(MASS) data(eurodist) OIF <- get.order(as.matrix(eurodist)) sid <- sample(1:nrow(OIF)) POI <- OIF[sid[1:1000],] result <- SOE(CM=POI, N=nrow(as.matrix(eurodist)),p=2, c=0.1,maxit =1000,report=100) plot(result$X,type="n",xlab="Dim. 1", ylab="Dim. 2") text(result$X,rownames(as.matrix(eurodist)),cex=1)
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