Evaluating the Performance of Machine Learning Approaches in Predicting Albanian Shkumbini River's Waters Using Water Quality Index Model
Lule Basha,
Bederiana Shyti,
Lirim Bekteshi
Abstract:A common technique for assessing the overall water quality state of surface water and groundwater systems globally is the water quality index (WQI) method. The aim of the research is to use four machine learning classifier algorithms: Gradient boosting, Naive Bayes, Random Forest, and K-Nearest Neighbour to determine which model was most effective at forecasting the various water quality index and classes of the Albanian Shkumbini River. The analysis was performed on the data collected during a 4-year period, … Show more
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