Eine Plattform für die Wissenschaft: Bauingenieurwesen, Architektur und Urbanistik
Eine Plattform für die Wissenschaft: Bauingenieurwesen, Architektur und Urbanistik
An Examination of Guaranteeing the Safety of Drinking Water using Machine Learning
Water is one of the greatest resources on earth. People need water to survive. It is important to know whether the water drank by people is potable or not - as the water is one of the necessary elements for live. Water resources of different regions should be analysed individually. This research study analyzes the water potability using the Indian Water Potability dataset from Kaggle. More specifically, this research study discusses about each water factor that influences the potability of water by statistical methods -Decision Tree algorithm. According to research, water features are independent to each other's. All the attributes must meet certain standards in order to obtain potable water.
An Examination of Guaranteeing the Safety of Drinking Water using Machine Learning
Water is one of the greatest resources on earth. People need water to survive. It is important to know whether the water drank by people is potable or not - as the water is one of the necessary elements for live. Water resources of different regions should be analysed individually. This research study analyzes the water potability using the Indian Water Potability dataset from Kaggle. More specifically, this research study discusses about each water factor that influences the potability of water by statistical methods -Decision Tree algorithm. According to research, water features are independent to each other's. All the attributes must meet certain standards in order to obtain potable water.
An Examination of Guaranteeing the Safety of Drinking Water using Machine Learning
Mishra, Varun (Autor:in) / Upadhyay, Soumya (Autor:in) / Jhaba, Pushpa (Autor:in) / Prajapati, Shobhit (Autor:in) / Gola, Kamal Kumar (Autor:in)
18.10.2023
457911 byte
Aufsatz (Konferenz)
Elektronische Ressource
Englisch
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