Splits factor levels into non-overlapping
clusters based on a factorMerger
object.
If a stat
is "loglikelihood"
or "p-value"
then performs bottom-up search through models
on the merging path until spots a model scored worse than
the given threshold (value
).
If stat = "GIC"
, value
is interpreted as
GIC penalty and optimal GIC model is returned.
getOptimalPartition(factorMerger, stat = "GIC", value = 2)
factorMerger | object of a class |
---|---|
stat | statistic used in the bottom-up search. Available statistics are:
|
value | cut threshold / GIC penalty |
Returns a vector with the final cluster names from the factorMerger
object.
By default, cutree
returns factor partition
corresponding to the optimal GIC model (with the lowest GIC).