A Machine Learning-Based Water Potability Prediction Model by Using Synthetic Minority Oversampling Technique and Explainable AI.

Patel, Jinal; Amipara, Charmi; Ahanger, Tariq Ahamed; Ladhva, Komal; Gupta, Rajeev Kumar; Alsaab, Hashem O; Althobaiti, Yusuf S; Ratna, Rajnish

Patel, Jinal; Amipara, Charmi; Ahanger, Tariq Ahamed; Ladhva, Komal; Gupta, Rajeev Kumar; Alsaab, Hashem O; Althobaiti, Yusuf S; Ratna, Rajnish.

Afiliação

Patel J; Department of Computer Science and Engineering Pandit Deendayal Energy University, Gandhinagar, Gujarat, India.
Amipara C; Department of Computer Science and Engineering Pandit Deendayal Energy University, Gandhinagar, Gujarat, India.
Ahanger TA; College of Computer Engineering and Sciences, Prince Sattam Bin Abdulaziz University, Saudi Arabia.
Ladhva K; Department of Computer Science and Engineering Pandit Deendayal Energy University, Gandhinagar, Gujarat, India.
Gupta RK; Department of Computer Science and Engineering Pandit Deendayal Energy University, Gandhinagar, Gujarat, India.
Alsaab HO; Department of Pharmaceutics and Pharmaceutical Technology, Taif University, Taif 21944, Saudi Arabia.
Althobaiti YS; Addiction and Neuroscience Research Unit, Taif University, Taif 21944, Saudi Arabia.
Ratna R; Addiction and Neuroscience Research Unit, Taif University, Taif 21944, Saudi Arabia.

Comput Intell Neurosci ; 2022: 9283293, 2022.

Article em En | MEDLINE | ID: mdl-36177311

Assuntos

Aprendizado de Máquina; Máquina de Vetores de Suporte; Previsões

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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Máquina de Vetores de Suporte / Aprendizado de Máquina Tipo de estudo: Prognostic_studies / Risk_factors_studies Idioma: En Revista: Comput Intell Neurosci Ano de publicação: 2022 Tipo de documento: Article

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