juggling {cccd} | R Documentation |
a resampled version of the CCCD classifier.
juggle(data, classes, sampled = TRUE, sample.dim = FALSE, num = 100, sample.proportion = 0.1, k = 2, method = NULL) juggle.classify(data,J,tdata,indices)
data,tdata |
training data from which to build the classifier. In the case
of |
classes |
class labels. |
sampled |
whether the data are subsampled. |
sample.dim |
if TRUE, the dimensions (variates) are also sampled. |
num |
number of juggles (resamples). |
sample.proportion |
proportion of the data to sample. If 1 or greater, the data are sampled with replacement. |
k |
number of variates to sample when |
J |
the juggled classifier. |
indices |
the indices of the juggles to use. |
method |
the method used for the distance.
See |
The idea of juggling is to sample the data, compute a CCCD classifier,
then repeat. The resampling is controled by the two sampling variables,
which basically determine whether the data are sampled with replacement,
or whether a subsample is used. If sample.dim
is TRUE, the
variates are also sampled, with k
indicating how many are sampled.
juggle.classify
returns a matrix holding the classification
probabilities for each observation in data
.
a list consisting of:
S |
the dominating sets. |
R |
the radii. |
dimension |
the dimension of the data. |
vars |
in the case of |
Only the indicies into the training data are stored in J
, which
is why the classifier requires the original training data in tdata
.
David J. Marchette, david.marchette@navy.mil