cloutput-class: "cloutput"
Description
Object returned by one of the classifiers (functions ending with CMA)Slots
learnind:- Vector of indices that indicates which observations
where used in the learning set.
y:- Actual (true) class labels of predicted observations.
yhat:- Predicted class labels by the classifier.
prob:- A
numeric matrix whose rows
equals the number of predicted observations (length of y/yhat)
and whose columns equal the number of different classes in the learning set.
Rows add up to one.
Entry j,k of this matrix contains the probability for the j-th
predicted observation to belong to class k.
Can be a matrix of NAs, if the classifier used does not
provide any probabilities method:- Name of the classifer used.
mode:character, one of "binary" (if the number of classes in the learning set is two)
or multiclass (if it is more than two).model:- List containing the constructed classifiers.
Methods
- show
- Use
show(cloutput-object) for brief information - ftable
- Use
ftable(cloutput-object) to obtain a confusion matrix/cross-tabulation
of y vs. yhat, s. ftable,cloutput-method. - plot
- Use
plot(cloutput-object) to generate a probability plot of the matrix
prob described above, s. plot,cloutput-method - roc
- Use
roc(cloutput-object) to compute the empirical ROC curve and the
Area Under the Curve (AUC) based on the predicted probabilities, s.roc,cloutput-method
See Also
clvarseloutput
compBoostCMA, dldaCMA, ElasticNetCMA,
fdaCMA, flexdaCMA, gbmCMA,
knnCMA, ldaCMA, LassoCMA,
nnetCMA, pknnCMA, plrCMA,
pls_ldaCMA, pls_lrCMA, pls_rfCMA,
pnnCMA, qdaCMA, rfCMA,
scdaCMA, shrinkldaCMA, svmCMA