AquaAugmentor: A Novel Feature Augmentation Algorithm for Water Potability Prediction
Access to potable water is crucial for health, economic development, and sustainability. However, accurately classifying water quality remains a significant challenge due to the complexity and variability of water source data. This paper addresses the challenge of predicting water potability through machine learning and deep learning algorithms. It introduces a novel feature augmentation algorithm, AquaAugmentor, to enhance the predictive performance of these models for low-dimensional datasets.
Record details
Published: 17 July 2026
Source: arXiv cs.AI
Category: Research
Topics: Healthcare · Environment
Retrieved: 20 July 2026
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ethics.ai (17 July 2026), “AquaAugmentor: A Novel Feature Augmentation Algorithm for Water Potability Prediction,” evidence record 11859, https://ethics.ai/record/11859 (originally published by arXiv cs.AI).
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