proDSval function

Classification of a test set by the evidential neural network classifier

proDSval classifies instances in a test set using the evidential neural network classifier.

proDSval(x, param, y = NULL)

Arguments

• x: Matrix of size n x d, containing the values of the d attributes for the test data.
• param: Neural network parameters, as provided by proDSfit.
• y: Optional vector of class labels for the test data. May be a factor, or a vector of integers from 1 to M (number of classes).

Returns

A list with three elements:

• m: Predicted mass functions for the test data. The first M columns correspond to the mass assigned to each class. The last column corresponds to the mass assigned to the whole set of classes.
• ypred: Predicted class labels for the test data.
• err: Test error rate (if the class label of test data has been provided).

Details

If class labels for the test set are provided, the test error rate is also returned.

Examples

## Glass dataset
data(glass)
xapp<-glass$x[1:89,]
yapp<-glass$y[1:89]
xtst<-glass$x[90:185,]
ytst<-glass$y[90:185]
## Initialization
param0<-proDSinit(xapp,yapp,nproto=7)
## Training
fit<-proDSfit(xapp,yapp,param0)
## Test
val<-proDSval(xtst,fit$param,ytst)
## Confusion matrix
table(ytst,val$ypred)

References

T. Denoeux. A neural network classifier based on Dempster-Shafer theory. IEEE Trans. on Systems, Man and Cybernetics A, 30(2):131--150, 2000.

See Also

proDSinit, proDSfit

Author(s)

Thierry Denoeux.