Predicts from a fitted classif object.
Classifier of functional data by kernel method using functional data object
of class classif. Returns the predicted classes using a previously trained model.
## S3 method for class 'classif' predict(object, new.fdataobj = NULL, type = "class", ...)
object |
Object |
new.fdataobj |
New functional explanatory data of |
type |
Type of prediction ("class or probability of each group membership"). |
... |
Further arguments passed to or from other methods. |
If type="class", produces a vector of predictions. If type="probs", a list with the following components is returned:
group.pred the vector of predictions.
prob.group the matrix of predicted probability by factor level.
Manuel Febrero-Bande, Manuel Oviedo de la Fuente manuel.oviedo@usc.es
Ferraty, F. and Vieu, P. (2006). Nonparametricc functional data analysis. Springer Series in Statistics, New York.
Ramsay, James O., and Silverman, Bernard W. (2006), Functional Data Analysis, 2nd ed., Springer, New York.
See also classif.np classif.glm,
classif.gsam and classif.gkam .
## Not run: data(phoneme) mlearn<-phoneme[["learn"]][1:100] glearn<-phoneme[["classlearn"]][1:100] # ESTIMATION knn out1=classif.knn(glearn,mlearn,knn=3) summary(out1) # PREDICTION knn mtest<-phoneme[["test"]][1:100] gtest<-phoneme[["classtest"]][1:100] pred1=predict(out1,mtest) table(pred1,gtest) # ESTIMATION kernel h=2^(0:5) # using metric distances computed in classif.knn out2=classif.kernel(glearn,mlearn,h=h,metric=out1$mdist) summary(out2) # PREDICTION kernel pred2=predict(out2,mtest) table(pred2,gtest) ## End(Not run)
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