classif.depth {fda.usc} | R Documentation |
Classifier from Functional Data
Description
Classification of functional data using maximum depth.
Usage
classif.depth(
group,
fdataobj,
newfdataobj,
depth = "RP",
par.depth = list(),
CV = "none"
)
Arguments
group |
Factor of length n |
fdataobj |
|
newfdataobj |
|
depth |
Type of depth function from functional data:
|
par.depth |
List of parameters for |
CV |
=“none” |
Value
-
group.est
: Vector of classes of train sample data. -
group.pred
: Vector of classes of test sample data. -
prob.classification
: Probability of correct classification by group. -
max.prob
: Highest probability of correct classification. -
fdataobj
:fdata
class object. -
group
: Factor of length n.
Author(s)
Febrero-Bande, M. and Oviedo de la Fuente, M.
References
Cuevas, A., Febrero-Bande, M. and Fraiman, R. (2007). Robust estimation and classification for functional data via projection-based depth notions. Computational Statistics 22, 3, 481-496.
Examples
## Not run:
data(phoneme)
mlearn<-phoneme[["learn"]]
mtest<-phoneme[["test"]]
glearn<-phoneme[["classlearn"]]
gtest<-phoneme[["classtest"]]
a1<-classif.depth(glearn,mlearn,depth="RP")
table(a1$group.est,glearn)
a2<-classif.depth(glearn,mlearn,depth="RP",CV=TRUE)
a3<-classif.depth(glearn,mlearn,depth="RP",CV=FALSE)
a4<-classif.depth(glearn,mlearn,mtest,"RP")
a5<-classif.depth(glearn,mlearn,mtest,"RP",CV=TRUE)
table(a5$group.est,glearn)
a6<-classif.depth(glearn,mlearn,mtest,"RP",CV=FALSE)
table(a6$group.est,glearn)
## End(Not run)