| calcAB | Determination of optimal coefficients for computing weights of evidence in logistic regression |
| calcm | Determination of optimal coefficients for computing weights of evidence in logistic regression |
| decision | Decision rules for evidential classifiers |
| EkNNfit | Training of the EkNN classifier |
| EkNNinit | Initialization of parameters for the EkNN classifier |
| EkNNval | Classification of a test set by the EkNN classifier |
| evclass | evclass: A package for evidential classification |
| glass | Glass dataset |
| ionosphere | Ionosphere dataset |
| proDSfit | Training of the evidential neural network classifier |
| proDSinit | Initialization of parameters for the evidential neural network classifier |
| proDSval | Classification of a test set by the evidential neural network classifier |
| RBFfit | Training of a radial basis function classifier |
| RBFinit | Initialization of parameters for a Radial Basis Function classifier |
| RBFval | Classification of a test set by a radial basis function classifier |
| vehicles | Vehicles dataset |