Výsledky vyhľadávania - "gradient boosting algorithms"

AN ENSEMBLE FRAMEWORK OF STACKED MULTI REGRESSORS AND GRADIENT BOOSTING ALGORITHMS WITH TUNED HYPER PARAMETERS – ENSTAR TO PREDICT EMPLOYEE PERFORMANCE SCORE USING HR ANALYTICS

Autori: null Philomine Roseline

Zdroj: International Journal of Applied Mathematics. 38:283-303

A Polynomial Features Extraction with SMOTE Model for Transmission Line Faults Detection & Classification with Gradient Boosting Algorithms

Autori: Sinivasa Reddy A D Madhu Sudhan Reddy B Rajasekhar a ďalší

Zdroj: 2025 5th International Conference on Soft Computing for Security Applications (ICSCSA). :1385-1389

Comparison of random forest and extreme gradient boosting algorithms in land cover classification in Van Yen district, Yen Bai province, Vietnam

Autori: Thanh Dong Khuc Ngoc Dung Luong Dieu Hue Dang a ďalší

Zdroj: Journal of Hydro-meteorology. :50-59

Gradient Boosting Algorithms for Day-ahead Residential Load Forecasting of Individual Household

Autori: Marios Saleptsis Marco Mussetta Sonia Leva

Zdroj: 2025 International Conference on Clean Electrical Power (ICCEP). :975-980

Early Detection of Student Dropout Risk via Hybrid Deep Learning and Gradient Boosting Algorithms

Autori: Vaibhav Rajput Aryan Singh Subhash Chand Gupta

Zdroj: 2025 International Conference on Engineering, Technology & Management (ICETM). :1-6

Classification and Prediction of Wafer Yield Using Gradient Boosting Algorithms: A Focus on Lithography Inline Parameters

Autori: Mohammed Nizamul Islam Md Tarekul Islam Maruf A Dhali

Zdroj: 2025 IEEE 4th International Conference on Computing and Machine Intelligence (ICMI). :1-6

Global Modeling and Predicting of Thermal Conductivity of Nanofluids Using an Ensemble of Different Tree-based Gradient Boosting Algorithms

Autori: Bayan Ali Alyousef

Zdroj: JORDANIAN JOURNAL OF ENGINEERING AND CHEMICAL INDUSTRIES (JJECI). :9-27

Bitcoin Mining Hardware Profitability Prediction Using Categorical Boosting and Extreme Gradient Boosting Algorithms

Autori: null Dimas Satria Prayoga Anggraini Puspita Sari Achmad Junaidi

Zdroj: Indonesian Journal of Electronics, Electromedical Engineering, and Medical Informatics. 7:167-177

Enhancing Fraud Detection with Gradient Boosting Algorithms in Credit Card Transactions

Autori: Sonam Juneja Amol Saurav Asmit Prabhakar a ďalší

Zdroj: 2025 International Conference on Cognitive Computing in Engineering, Communications, Sciences and Biomedical Health Informatics (IC3ECSBHI). :903-910

Prediction of Imbalance Prices Through Gradient Boosting Algorithms: An Application to the Greek Balancing Market

Autori: Konstantinos Plakas Nikos Andriopoulos Dimitrios Papadaskalopoulos a ďalší

Zdroj: IEEE Access, Vol 13, Pp 103968-103981 (2025)

Predmety: machine learning, power system, Electricity market, Electrical engineering. Electronics. Nuclear engineering, balancing market, probabilistic forecasting, TK1-9971

Prístupová URL adresa: https://doaj.org/article/0c3f5450ea93452582449aba74bb30af

Evaluating the efficacy of gradient boosting algorithms in retail demand forecasting: a case study of triumph international

Autori: Schirripa, Monica Belo, Rodrigo RUN

Prispievatelia: Schirripa, Monica Belo, Rodrigo RUN

Predmety: Demand forecasting, Machine learning, Time-series forecasting, Fashion retail, Master thesis, Gradient boosting, Domínio/Área Científica::Ciências Sociais::Economia e Gestão

Popis súboru: application/pdf

Dostupnosť: http://hdl.handle.net/10362/176920

Flood-prone area mapping using a synergistic approach with swarm intelligence and gradient boosting algorithms

Autori: Seyed Vahid Razavi-Termeh Abolghasem Sadeghi-Niaraki Sani I. Abba a ďalší

Zdroj: Scientific Reports. 15

Earthquake Prediction Model Using Random Forest and Gradient Boosting Algorithms

Autori: D. Bujji Babu MVN L Revathi M. Senthil a ďalší

Zdroj: 2024 9th International Conference on Communication and Electronics Systems (ICCES). :1597-1607

Breast Cancer Classification Using Gradient Boosting Algorithms Focusing on Reducing the False Negative and SHAP for Explainability

Autori: Pinheiro, João Manoel Herrera Becker, Marcelo

Zdroj: Inteligencia Artificial. 28:63-80

Predmety: Machine Learning, FOS: Computer and information sciences, Artificial Intelligence (cs.AI), Artificial Intelligence, FOS: Biological sciences, Computers and Society (cs.CY), 0202 electrical engineering, electronic engineering, information engineering, Quantitative Methods, 02 engineering and technology, Computers and Society, Quantitative Methods (q-bio.QM), 3. Good health, Machine Learning (cs.LG)

Prístupová URL adresa: http://arxiv.org/abs/2403.09548

Evaluation of pedotransfer functions to estimate saturated hydraulic conductivity using machine learning with random forest and gradient boosting algorithms

Autori: Ahmed Y. Mady Mhamoud A. Abdelhamid Lina A. Shalaby a ďalší

Zdroj: Soil and Environment. 43:268-277

Optimizing Gradient Boosting Algorithms for Obesity Risk Prediction: A Comparative Analysis of XGBoost, LightGBM, and CatBoost Models

Autori: Eshika Jain Amanveer Singh

Zdroj: 2024 International Conference on Cybernation and Computation (CYBERCOM). :320-324

Induction Motor Multi Incipient Fault Detection based on Gradient Boosting Algorithms

Autori: Rehaan Hussain Mohammad AlShaikh Saleh Shady S. Refaat

Zdroj: IECON 2024 - 50th Annual Conference of the IEEE Industrial Electronics Society. :1-6

Enhanced Ransomware Detection Using Gradient Boosting Algorithms: A Cybersecurity Dataset Approach

Autori: Anshika Sharma Himanshi Babbar Amit Kumar Vats

Zdroj: 2024 5th IEEE Global Conference for Advancement in Technology (GCAT). :1-5

Imbalanced rock burst assessment using variational autoencoder-enhanced gradient boosting algorithms and explainability

Autori: Lin, S Liang, Z Dong, M a ďalší

Prispievatelia: Lin, S Liang, Z Dong, M a ďalší

Zdroj: Underground Space, Vol 17, Iss, Pp 226-245 (2024)

Predmety: VAE, Ensemble learning, Gradient boosting, Explainable artificial intelligence (XAI), 0211 other engineering and technologies, 0202 electrical engineering, electronic engineering, information engineering, TA703-712, Rock burst, Engineering geology. Rock mechanics. Soil mechanics. Underground construction, 02 engineering and technology

Prístupová URL adresa: https://doaj.org/article/43bd135836774e6a8f26fd3bd4cabfb7

Adverse Media Classification: A New Era of Risk Management with XGBoost and Gradient Boosting Algorithms

Autori: Reza Juliandri Monika Evelin Johan Jansen Wiratama a ďalší

Zdroj: 2024 5th International Conference on Big Data Analytics and Practices (IBDAP). :18-21