“This work demonstrates that combining interpretable fuzzy rules with feature importance explanations enhances both utility and trust, providing practical insights for XAI deployment in maternal healthcare.”

“The paper's core contribution is the multi-objective optimization framework using NSGA-II to generate a Pareto front of trade-off solutions, allowing for a balanced compromise between competing fairness criteria.”

“Tree-based ensemble methods, including Random Forest and XGBoost, proved inherently robust to this violation, achieving an R-squared of 0.765 and RMSE of 0.731 logP units on the test set.”

“XGBoost reaches 99.59% accuracy with microsecond-level inference using an augmented and LLM-filtered dataset.”

“The paper concludes that all methods (linear regression, xgboost, and a convolutional neural network) can achieve the best results under appropriate circumstances, and that the amount of information needed for good results depends on the strength of the peer pressure effect.”

“The idea is to provide a lightweight way to: - upload a time series dataset, - train a set of baseline and widely used models (e.g. linear regression with lags, XGBoost, Prophet), - compare their forecasts and evaluation metrics on the same split.”

“XGBoost achieved the strongest performance.”

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