Prunnig Algorithm of Generation a Minimal Set of Rule Reducts Based on Rough Set Theory

TL;DR

This paper introduces the PRG algorithm, a novel pruning method using tree structures to efficiently generate minimal rule reducts in Rough Set Theory, improving upon existing RG and MRG algorithms.

Contribution

The paper presents a new pruning algorithm (PRG) that enhances rule reduct generation efficiency using tree structures, offering an alternative to established methods.

Findings

PRG algorithm effectively reduces computational complexity.

PRG outperforms RG and MRG algorithms in experiments.

Tree structure utilization improves rule reduct generation.

Abstract

In this paper it is considered rule reduct generation problem, based on Rough Set Theory. Rule Reduct Generation (RG) and Modified Rule Generation (MRG) algorithms are well-known. Alternative to these algorithms Pruning Algorithm of Generation A Minimal Set of Rule Reducts, or briefly Pruning Rule Generation (PRG) algorithm is developed. PRG algorithm uses tree structured data type. PRG algorithm is compared with RG and MRG algorithms