evclass: evclass: A package for evidential classification

In evclass: Evidential Distance-Based Classification

evclass: A package for evidential classification

Description

The evclass package currently contains functions for three evidential classifiers: the evidential K-nearest neighbor (EK-NN) rule (Denoeux, 1995; Zouhal and Denoeux, 1998), the evidential neural network (Denoeux, 2000) and the RBF classifier with weight-of-evidence interpretation (Denoeux, 2019; Huang et al., 2022), as well as methods to compute output mass functions from trained logistic regression or multilayer classifiers as described in (Denoeux, 2019). In contrast with classical statistical classifiers, evidential classifiers quantify the uncertainty of the classification using Dempster-Shafer mass functions.

Details

The main functions are: EkNNinit, EkNNfit and EkNNval for the initialization, training and evaluation of the EK-NN classifier; proDSinit, proDSfit and proDSval for the evidential neural network classifier; decision for decision-making; RBFinit, RBFfit and RBFval for the RBF classifier; calcAB and calcm for computing output mass functions from trained logistic regression or multilayer classifiers.

References

T. Denoeux. A k-nearest neighbor classification rule based on Dempster-Shafer theory. IEEE Transactions on Systems, Man and Cybernetics, 25(05):804–813, 1995.

T. Denoeux. Analysis of evidence-theoretic decision rules for pattern classification. Pattern Recognition, 30(7):1095–1107, 1997.

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

L. M. Zouhal and T. Denoeux. An evidence-theoretic k-NN rule with parameter optimization. IEEE Transactions on Systems, Man and Cybernetics Part C, 28(2):263–271,1998.

T. Denoeux. Logistic Regression, Neural Networks and Dempster-Shafer Theory: a New Perspective. Knowledge-Based Systems, Vol. 176, Pages 54–67, 2019.

L., S. Ruan, P. Decazes and T. Denoeux. Lymphoma segmentation from 3D PET-CT images using a deep evidential network. International Journal of Approximate Reasoning, Vol. 149, Pages 39-60, 2022.

See Also

EkNNinit, EkNNfit, EkNNval, proDSinit, proDSfit, proDSval, RBFinit, RBFfit and RBFval, decision, calcAB, calcm.

evclass documentation built on Nov. 9, 2023, 5:08 p.m.