| 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 |