Unsupervised learning on Ghana soil data identifies a small set of anomalous heavy metal samples that match elevated health risk indices.
Framework for metals risk assessment,
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Anomaly Detection in Soil Heavy Metal Contamination Using Unsupervised Learning for Environmental Risk Assessment
Unsupervised learning on Ghana soil data identifies a small set of anomalous heavy metal samples that match elevated health risk indices.