Air Quality Modelling by Decision Trees and Hybrid Rough Sets - Decision Trees

Abstract

This paper deals with air quality modelling by decision trees and by hybrid rough sets-decision trees in the Czech Republic. We focused on daily observations of air polluting substances concentrations in one of the cities in the Pardubice region. After data collection, data description, and data pre-processing, we worked on the creation of classification models and the analysis of the achieved results. As modelling algorithms we selected C5.0 algorithm, boosting, and CHAID method. Finally is proposed hybrid model, where Rough Sets algorithm for the purpose of attributes reduction is used.