Investigating the Performance of the Combined Dagging Method with the Hoeffding Tree Base Algorithm in the Qualitative Classification of Drinking Water

For the effective qualitative management of drinking water, it is necessary to estimate the level of water pollution. In this research, to calculate the quality index of drinking water from the chemical parameters of Total Hardness, Alkalinity, Electrical Conductivity, Total Dissolved Solids, Calcium, Sodium, Magnesium, Potassium, Chlorine, Carbonate, Bicarbonate, and Sulfate in the hydrometric station of Bagh Kelayeh, Qazvin province used in the statistical period of 23 years (1998-2020). According to the calculated numerical values ​​and existing standards, water quality classified into two classes, good and excellent. To predict the quality class of drinking water based on chemical parameters, different combinations of parameters were considered in the form of several scenarios. In this regard, correlation and relief algorithms were used to select different scenarios. Hoeffding tree was used as a basic model for classifying water quality based on different combinations of parameters. Also, the performance of the combined Dagging approach in improving the results was evaluated. The results showed that the combined Dagging improves the water quality classification results. Scenario 6 Dagging with Hoeffding tree base algorithm, including HCO3, Ca, SO3, TDS, EC and TH parameters, with Kappa = 1, was introduced as the best method which is able to classify test samples correctly.