A Novel Feature-Engineered–NGBoost Machine-Learning Framework for Fraud Detection in Electric Power Consumption Data [PDF]
Sensors, 2021 This study presents a novel feature-engineered–natural gradient descent ensemble-boosting (NGBoost) machine-learning framework for detecting fraud in power consumption data.
Saddam Hussain +2 more
exaly +9 more sources
NGBoost Classifier Using Deep Features for Pneumonia Chest X-Ray Classification
Applied Sciences (Switzerland)Pneumonia remains a major global health concern, leading to significant mortality and morbidity. The identification of pneumonia by chest X-rays can be difficult due to its similarity to other lung disorders.
Mahanand Belathur Suresh +2 more
exaly +5 more sources
Buildings, 2023 Multi-objective optimization problems (MOPs) in structural engineering arise as a significant challenge in achieving a balance between prediction accuracy and efficiency of the surrogate models, which are conventionally adopted as mechanics-driven models
Shixue Liang, Yuanxie Shen, Zhengyu Fei
exaly +5 more sources
Uncertainty aware and explainable construction cost prediction using a hybrid probabilistic learning model [PDF]
Scientific ReportsThis paper presents a unified probabilistic framework for construction cost forecasting, NGBoost-ETR (Natural Gradient Boosting with Extra Trees base learners) that delivers predictive accuracy, calibrated uncertainty, and SHAP-based interpretability ...
Lifei Chen +7 more
doaj +3 more sources
Accurate and interpretable prediction of chemical oxygen demand using explainable boosting algorithms with SHAP analysis [PDF]
Scientific ReportsAccurate prediction of Chemical Oxygen Demand (COD) is vital for effective water quality management and pollution control. This study compares six ensemble boosting models, AdaBoost, CatBoost, XGBoost, LightGBM, HistGBRT, and NGBoost, for estimating COD ...
Khaled Merabet +8 more
doaj +3 more sources
Neural-NGBoost: Natural Gradient Boosting With Neural Network Base Learners
ICT ExpressNGBoost has shown promising results in probabilistic and point estimation tasks. However, it is vague still whether this method can be scalable to neural architecture system since its base learner is based on decision trees.
Seung-Hwan Bae
exaly +5 more sources
Underground Space (China)This study aims to develop and evaluate a natural gradient boosting (NGBoost) model optimized with Optuna for estimating ground settlement during tunnel excavation, incorporating Shapley additive explanations (SHAP) to perform interpretability analysis ...
Yuxin Chen +2 more
exaly +4 more sources
Interpretable wind power probabilistic prediction based on NGBoost
Zhejiang dianli, 2023 To realize the probabilistic prediction of wind power and analyze the influencing factors of the prediction results， this paper proposes a probabilistic prediction method of wind power based on natural gradient boosting （NGBoost） and takes account of ...
LI Bingsheng +2 more
doaj +2 more sources
Uncertainty Estimation in Predicting River Discharge Using Probabilistic Machine Learning and Conformal Prediction [PDF]
SensorsReliable streamflow forecasting with quantified uncertainty is essential for water resource management, flood mitigation, and climate adaptation in semi-arid regions.
Erfan Abdi +4 more
doaj +2 more sources
A Hybrid Approach for Predicting Corporate Financial Risk: Integrating SMOTE-ENN and NGBoost
IEEE Access, 2023 The financial condition of an enterprise is a critical factor in determining its viability and long-term prospects, and it also directly affects the interests of stakeholders such as investors and creditors.
Yikun Zhu +5 more
doaj +3 more sources