Build a naive bayes classifier on continuous descriptors. TANAGRA implementation of naive bayes classifier handles only discrete attributes, we needto discretize continuous descriptors before use them.
Because we are in a supervised learning context, we must use a superviseddiscretization algorithm such as Fayyad and Irani’s state-of-the-art MDLPC algorithm.
Keywords: contextula discretization, naive bayes classifier, cross-validation
Components: MDLPC, Supervised Learning, Naive bayes, Cross-validation
Tutorial: enSupervisedDiscretisation.pdf
Dataset: breast.bdm
References:
U. Fayyad et K. Irani, « Multi-interval discretization of continuous-valued attributes for classification learning », in Proc. of IJCAI, pp.1022-1027, 1993.
