Predict the neuron where a new observation is classified
# S3 method for somRes predict(object, x.new = NULL, ..., radius = 0)
a new observation (optional). Default values is NULL which corresponds to performing prediction on the training dataset.
current radius used to perform soft affectation (when
affectation = "heskes", see
initSOM for further details
about Heskes' soft affectation). Default value is 0,
which corresponds to a hard affectation.
predict.somRes returns the number of the neuron to which the
new observation is assigned (i.e., neuron with the closest prototype).
When the algorithm's type is
x.new must be the
original contingency table passed to the algorithm.
The number of columns of the new observations (or its length if only
one observation is provided) must match the number of columns of the data set
given to the SOM algorithm (see