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Author

Pushpalata Pujari

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Conference Aug 2026

Statistical and Spatial Evaluation of Machine Learning Models for Imbalanced Soil Heavy Metal Contamination Classification

Soil heavy metal contamination poses significant environmental and public health risks, requiring accurate and interpretable classification methods for effective risk assessment. This study presents a comparative evaluation of five machine learning models—Random Forest, XGBoost, LightGBM, TabNet, and Multi-Layer Percep...

Anita Sidar, Pushpalata Pujari · 0 citations
Jul 2026

An optimized stacking ensemble framework with multi-layer explainable AI for soil heavy metal contamination classification

A transformer-driven stacking ensemble framework for multiclass soil contamination classification that is optimized using Genetic Algorithms (GA) in order to overcome difficulties and make the predictions easier to understand and more aware of risks is suggested.

Anita Sidar, Pushpalata Pujari · 0 citations

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