Description Usage Arguments Value Author(s) References See Also Examples
Assigns clusters and distances to cluster centers in the corresponding subspaces for new data according to a subspace clustering model of class orclus
.
1 2 |
object |
Model resulting from a call of |
newdata |
A matrix or data frame to be clustered by the given model. |
... |
Currently not used. |
distances |
A matrix where coloumns are the distances to all cluster centers in the corresponding subspaces for the new data. |
cluster |
The resulting cluster labels for the new data. |
Gero Szepannek
Aggarwal, C. and Yu, P. (2000): Finding generalized projected clusters in high dimensional spaces, Proceedings of ACM SIGMOD International Conference on Management of Data, pp. 70-81.
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 | # generate simple artificial example of two clusters
clus1.v1 <- runif(100)
clus2.v1 <- runif(100)
xample <- rbind(cbind(clus1.v1, 0.5 - clus1.v1), cbind(clus2.v1, -0.5 + clus2.v1))
orclus.res <- orclus(x = xample, k = 2, l = 1, k0 = 8, a = 0.5)
# generate new data and predict it using the
newclus1.v1 <- runif(100)
newclus2.v1 <- runif(100)
true.clusterids <- rep(1:2, each = 100)
xample2 <- rbind(cbind(newclus1.v1, 0.5 - newclus1.v1),
cbind(newclus2.v1, -0.5 + newclus2.v1))
orclus.prediction <- predict(orclus.res, xample2)
table(orclus.prediction$cluster, true.clusterids)
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