Algorithms (GA) for feature selection with LightGBM for classification. The GA component identifies the most relevant features …, while LightGBM ensures high prediction accuracy and computational efficiency. The model was evaluated on two datasets …, Precision, Recall, F1-Score, and AUC. The proposed GA +LightGBM model achieved an AUC of 0.94 and F1-Score of 0.87 on the HR …

This article presents a comprehensive study on developing a predictive product pricing model using LightGBM, a machine … principles of LightGBM, including decision trees, boosting, and gradient descent, and then delves into the method's unique … demonstrated through a comparative analysis with XGBoost, highlighting LightGBM's enhanced efficiency and slight improvement in …

-learning models with the baseline random forest, LightGBM, support vector regression, and k-nearest neighborhood models using mean … BiGRU model performs best for gold, with an MAE of 15.188 using a 30-day input sequence. Furthermore, LightGBM exhibits …

This article presents a comprehensive study on developing a predictive product pricing model using LightGBM, a machine … principles of LightGBM, including decision trees, boosting, and gradient descent, and then delves into the method's unique … demonstrated through a comparative analysis with XGBoost, highlighting LightGBM's enhanced efficiency and slight improvement in …

machine learning methods, including Random Forest, LightGBM, and CatBoost, alongside logistic regression models. To address …

telecommunications industry by introducing a combined method of the LightGBM model and SHAP framework, providing a thorough analysis of …