Water Clarity Reinvented: Predictive Insights with Bagging Classifiers

To keep people healthy and alive, we need to provide clean water. In managing water resources and reducing pollution, it's important to predict water quality measurements. We look at various water quality factors like pH levels, oxygen in the water, cloudiness, and nutrient amounts in different areas. Bagging classifiers are a popular machine learning technique used in this study to improve the accuracy and reliability of a model. We expect to have 76% accuracy after using the bagging classifiers. This work uses different methods to show various learning strategies, like Bagging Classifiers, to improve water quality. Our work helps improve how we check water quality. This is important for managing the environment well and ensuring everyone has access to clean water. We use different methods, including a technique called ensemble learning, to do this.