Nature

Machine learning for quantitative LIBS analysis of aluminum alloys: a comparison of random forest, gradient boosting, and extremely randomized trees

Laser-induced breakdown spectroscopy (LIBS) is a versatile technique for characterizing materials and analyzing elements, but it is limited in its quantitative accuracy due to nonlinear effects. This ...
GitHub

Gradient Boosting Reinforcement Learning (GBRL)

GBRL is a Python-based Gradient Boosting Trees (GBT) library, similar to popular packages such as XGBoost, CatBoost, but specifically designed and optimized for reinforcement learning (RL). GBRL is ...
IEEE

Analysis of Global Air-pollution Data 2025 By ML and Python

Abstract: Air pollution poses a critical global health challenge requiring accurate prediction systems. This paper evaluates eleven machine learning models for air quality classification using the ...
Scientific Research Publishing

Extra Trees Model for Heart Disease Prediction ()

1 Computer Science Department, Babcock University, Ilishan-Remo, Ogun State, Nigeria. 2 Computer Science Department, Adeleke University, Ede, Osun State, Nigeria. 3 Department of Applied Mathematics, ...
Visual Studio Magazine

Binary Classification Using LightGBM

Dr. James McCaffrey from Microsoft Research presents a full-code, step-by-step tutorial on using the LightGBM tree-based system to perform binary classification (predicting a discrete variable that ...
Visual Studio Magazine

Regression Using LightGBM

Dr. James McCaffrey of Microsoft Research presents a full-code, step-by-step tutorial on this powerful machine learning technique used to predict a single numeric value. A regression problem is one ...
IEEE

Utilizing Machine Learning Algorithms to Predict Accuracy of the Index of Relative Tectonic Activity (IRTA), Dhansiri (North) River Basin in India and Bhutan

Abstract: A river tries to maintain a dynamic equilibrium state by adjusting different controlling factors. A significant change in one of the controlling factors will dictate modifications in the ...
Nature

Computational intelligence modeling of hyoscine drug solubility and solvent density in supercritical processing: gradient boosting, extra trees, and random forest models

The poor water solubility of newly discovered medicines has been a major issue for pharmaceutical industry, and various techniques have been explored and developed to enhance the solubility of drugs ...
Frontiers

Interaction Analysis Based on Shapley Values and Extreme Gradient Boosting: A Realistic Simulation and Application to a Large Epidemiological Prospective Study

SHapley Additive exPlanations (SHAP) based on tree-based machine learning methods have been proposed to interpret interactions between exposures in observational studies, but their performance in ...
Frontiers

Gradient Boosting Machine Learning Model for Defective Endometrial Receptivity Prediction by Macrophage-Endometrium Interaction Modules

A receptive endometrium is a prerequisite for successful embryo implantation. Mounting evidence shows that nearly one-third of infertility and implantation failures are caused by defective endometrial ...