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This project implements a fully automated pipeline for solving the credit scoring task based on an ensemble of six CatBoost models, optimized for hyperparameters with Optuna. For practical application ...

Interpretable Machine Learning Framework for Biomass–Plastic Co-gasification. This graphical workflow illustrates the development of an interpretable machine learning framework to predict syngas ...

LinkedIn support accidentally revealed its algorithm: it tracks "viewer tolerance," reducing visibility for authors whose posts are consistently ignored. To succeed, diversify content types weekly, ...

ABSTRACT: Rainfall-induced landslides threaten mountainous regions globally, yet existing models face challenges in real-time, large-scale prediction due to dependency on post-event data. This study ...

This study applies machine learning techniques, including CatBoost, Random Forest, and XGBoost, to predict porosity using experimental data from 252 research papers covering ceramics, polymers, and ...

The field of human microbiome research is rapidly expanding beyond the gut and into the facial skin care industry. However, there is still no established criterion to define the objective relationship ...

ABSTRACT: Missing data remains a persistent and pervasive challenge across a wide range of domains, significantly impacting data analysis pipelines, predictive modeling outcomes, and the reliability ...

LinkedIn's algorithm prioritizes ads & sponsored content, hurting organic reach for creators. To adapt: share niche expertise, use authentic images, craft strong hooks, write longer comments, engage ...