Algorithms of designing decision trees from indeterm soft sets

Caballero E.G.; Moscoso-Paucarchuco K.M.; Hernandez N.B.; Torres L.J.C.; Leyva M.; Gómez Rodríguez V.G. · Neutrosophic and Plithogenic Inventory Models for Applied Mathematics (2025) · DOI: 10.4018/979-8-3693-3204-7.ch022

Resumen

Since their creation, soft sets have served as a technique to model different situations of uncertainty. Furthermore, they have been extended to or hybridized with other theories of uncertainty. One of them is the introduction of IndetermSoft sets, where indeterminacy is incorporated into at least one of the components of the soft sets. Decision trees are well-known tools that allow an object or entity to be classified by the data measured according to some attributes. The simplest algorithms for creating decision trees are ID3 and C4.5. The purpose of this chapter is to extend these two algorithms in the area of uncertainty and indeterminacy for data represented in the form of IndetermSoft sets. In this way it is possible to obtain decision rules when there is indeterminacy in the data.

Instituciones: Universidad Nacional Autónoma Altoandina de Tarma