Results 1 to 10 of about 72,345 (262)

Health Risk Classification Using XGBoost with Bayesian Hyperparameter Optimization

Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi)
Health risk classification is important. However, health risk classification is challenging to address using conventional analytical techniques.
Syaiful Anam, Imam Nurhadi Purwanto, Dwi Mifta Mahanani, Feby Indriana Yusuf, Hady Rasikhun   +4 more
doaj   +3 more sources

Classification of UNSW-NB15 dataset using Exploratory Data Analysis using Ensemble Learning [PDF]

EAI Endorsed Transactions on Industrial Networks and Intelligent Systems, 2021
Recent advancements in machine learning have made it a tool of choice for different classification and analytical problems. This paper deals with a critical field of computer networking: network security and the possibilities of machine ...
Neha Sharma, Narendra Yadav, Saurabh Sharma   +2 more
doaj   +1 more source

Comparison of some non-linear functions to describe the growth for Linda geese with CART and XGBoost algorithms

Czech Journal of Animal Science, 2022
The aim of this study was to determine the best non-linear function describing the growth of the Linda goose breed. To achieve this aim, five non-linear functions, such as exponential, logistic, von Bertalanffy, Brody and Gompertz, were employed to ...
Cem Tirink, Hasan Önder, Sabri Yurtseven, Zeliha Kaya Akil   +3 more
doaj   +1 more source

Prediction Method of Aircraft Dynamic Taxi Time Based on XGBoost

Hangkong gongcheng jinzhan, 2022
Accurate and dynamic prediction of aircraft arrival and departure taxi time can effectively improve the operation efficiency of the airport. An aircraft dynamic taxi time prediction method based on XGBoost is proposed for the first time.
ZHAO Zheng, FENG Shicheng, SONG Meiwen, HU Li, LU Sha   +4 more
doaj   +1 more source

Application of Bayesian optimized XGBoost in seismic interpretation of small-scale faults

Meitan xuebao, 2023
In order to further improve the identification accuracy of small-scale faults in seismic interpretation, Bayesian optimized extreme gradient boosting (XGBoost) model was constructed to recognize small-scale faults across coalbeds using reduced seismic ...
Changwei DING, Xin WANG, Tongjun CHEN, Ting YU   +3 more
doaj   +1 more source

Machine Learning XGBoost Method for Detecting Mangrove Cover Using Unmanned Aerial Vehicle Imagery

Jambura Geoscience Review, 2023
The mangrove ecosystem can be understood as a unique and different type of ecosystem that can benefit the surrounding ecosystem from the socio-economic and ecological perspective.
Minati Minati, Iksal Yanuarsyah, Sahid Agustian Hudjimartsu   +2 more
doaj   +1 more source

An interpretable machine learning model for predicting cavity water depth and cavity length based on XGBoost–SHAP

Journal of Hydroinformatics, 2023
In contrast to the traditional black box machine learning model, the white box model can achieve higher prediction accuracy and accurately evaluate and explain the prediction results.
Tiexiang Mo, Shanshan Li, Guodong Li
doaj   +1 more source

PRIP: A Protein-RNA Interface Predictor Based on Semantics of Sequences

Life, 2022
RNA–protein interactions play an indispensable role in many biological processes. Growing evidence has indicated that aberration of the RNA–protein interaction is associated with many serious human diseases. The precise and quick detection of RNA–protein
You Li, Jianyi Lyu, Yaoqun Wu, Yuewu Liu, Guohua Huang   +4 more
doaj   +1 more source

XGBoost

, 2021
Multi-fidelity tabular data for XGBoost hyperparameter space for ...
Neeratyoy Mallik (11224725)
core   +1 more source

XGBoost

, 2022
Tianqi Chen, Tong He XGBoost: eXtreme Gradient Boosting; R Package Version 1.5.0.1; 8 November, 2021; pp.
Huijing Wang (11922680)
core   +1 more source