Results 11 to 20 of about 126,268 (270)

Correction to Extreme Gradient Boosting as a Method for Quantitative Structure–Activity Relationships

, 2020
Correction to Extreme Gradient Boosting as a Method for Quantitative Structure–Activity ...
Eric Gifford (1483846), Robert P. Sheridan (1271010), Andy Liaw (783113), Junshi Ma (8352051), Min Wang (21070)   +4 more
core   +30 more sources

A tree based eXtreme Gradient Boosting (XGBoost) machine learning model to forecast the annual rice production in Bangladesh [PDF]

PLoS One, 2023
In this study, we attempt to anticipate annual rice production in Bangladesh (1961–2020) using both the Autoregressive Integrated Moving Average (ARIMA) and the eXtreme Gradient Boosting (XGBoost) methods and compare their respective performances. On the
M. Noorunnahar, A. Chowdhury, F. A. Mila
semanticscholar   +2 more sources

Bioactive Molecule Prediction Using Extreme Gradient Boosting [PDF]

Molecules, 2016
Following the explosive growth in chemical and biological data, the shift from traditional methods of drug discovery to computer-aided means has made data mining and machine learning methods integral parts of today’s drug discovery process. In this paper, extreme gradient boosting (Xgboost), which is an ensemble of Classification and Regression Tree ...
Ismail Babajide Mustapha, Faisal Saeed
openaire   +4 more sources

Predicting energy use in construction using Extreme Gradient Boosting [PDF]

PeerJ Computer Science, 2023
Annual increases in global energy consumption are an unavoidable consequence of a growing global economy and population. Among different sectors, the construction industry consumes an average of 20.1% of the world’s total energy. Therefore, exploring methods for estimating the amount of energy used is critical.
Jiaming Han, Kunxin Shu, Zhenyu Wang
openaire   +5 more sources

Investigation on eXtreme Gradient Boosting for cutting force prediction in milling

Journal of Intelligent Manufacturing, 2023
Accurate prediction of cutting forces is critical in milling operations, with implications for cost reduction and improved manufacturing efficiency. While traditional mechanistic models provide high accuracy, their reliance on extensive milling data for force coefficient fitting poses challenges.
Thomas Heitz, Ning He, Addi Ait-Mlouk, Daniel Bachrathy, Ni Chen, Guolong Zhao, Liang Li   +6 more
openaire   +3 more sources

Extreme Gradient Boosting Combined with Conformal Predictors for Informative Solubility Estimation [PDF]

Molecules, 2023
We used the extreme gradient boosting (XGB) algorithm to predict the experimental solubility of chemical compounds in water and organic solvents and to select significant molecular descriptors. The accuracy of prediction of our forward stepwise top-importance XGB (FSTI-XGB) on curated solubility data sets in terms of RMSE was found to be 0.59–0.76 Log ...
Ozren Jovic, Rabah Mouras
openaire   +6 more sources

Carbon price prediction based on decomposition technique and extreme gradient boosting optimized by the grey wolf optimizer algorithm [PDF]

Sci Rep, 2023
It is essential to predict carbon prices precisely in order to reduce CO_2 emissions and mitigate global warming. As a solution to the limitations of a single machine learning model that has insufficient forecasting capability in the carbon price ...
M. Feng, Yonghui Duan, Xiang Wang, Jingyi Zhang, Lanlan Ma   +4 more
semanticscholar   +2 more sources

Forecasting Enterprises Bankruptcy by Extreme Gradient Boosting

Bulletin of the South Ural State University. Series "Computational Mathematics and Software Engineering", 2020
Мокеев Владимир Викторович, д.т.н., старший научный сотрудник, профессор кафедры информационных технологии в экономике, Южно-Уральского государственный университет (национальный исследовательский университет) (Челябинск, Российская Федерация) Войтецкий ...
Войтецкий, Р.В., Мокеев, В.В., Mokeyev, V.V., Voitetckiy, R.V.   +3 more
openaire   +3 more sources

GWO-XGB: Grey Wolf Optimization-based eXtreme Gradient Boosting for Hypertension Prediction in Bangladesh

, 2021
Hypertension is rapidly increasing day by day worldwide as well as in Bangladesh. The majority of people in our country die due to hypertension. So, early prediction of this disease is a very important task that may reduce the number of affected patients.
Shahriar Sikder, Tuli, Anamika Biswas, Md. Ashfikur Rahman, Md. Abdul Awal, Rahman, Md Ashfikur, Bulbul, Abdullah Al-Mamun, Tahsin, Tasfia, Sikder, Shahriar, Awal, Md Abdul, Tasfia Tahsin, Khondoker Mirazul Mumenin, Abdullah Al-Mamun Bulbul, Mumenin, Khondoker Mirazul, Pinki, Farhana Tazmim, Anamika Biswas Tuli, Farhana Tazmim Pinki   +15 more
core   +1 more source

Boosting Privately: Federated Extreme Gradient Boosting for Mobile Crowdsensing

2020 IEEE 40th International Conference on Distributed Computing Systems (ICDCS), 2020
Recently, Google and other 24 institutions proposed a series of open challenges towards federated learning (FL), which include application expansion and homomorphic encryption (HE). The former aims to expand the applicable machine learning models of FL. The latter focuses on who holds the secret key when applying HE to FL.
Yang Liu 0118, Zhuo Ma 0001, Ximeng Liu, Siqi Ma, Surya Nepal, Robert H. Deng, Kui Ren 0001   +6 more
openaire   +3 more sources