Results 31 to 40 of about 150,441 (331)

Computer-aided diagnosis of lung nodule using gradient tree boosting and Bayesian optimization

, 2017
We aimed to evaluate computer-aided diagnosis (CADx) system for lung nodule classification focusing on (i) usefulness of gradient tree boosting (XGBoost) and (ii) effectiveness of parameter optimization using Bayesian optimization (Tree Parzen Estimator,
Kojima, Ryosuke, Kuroda, Tomohiro, Nishio, Mizuho, Nishizawa, Mitsuo, Sugiyama, Osamu, Togashi, Kaori, Yakami, Masahiro   +6 more
core   +2 more sources

Comprehensive Analysis of Random Forest and XGBoost Performance with SMOTE, ADASYN, and GNUS Under Varying Imbalance Levels

Technologies
This study examines the efficacy of Random Forest and XGBoost classifiers in conjunction with three upsampling techniques—SMOTE, ADASYN, and Gaussian noise upsampling (GNUS)—across datasets with varying class imbalance levels, ranging from moderate to ...
Mehdi Imani, Ali Beikmohammadi, H. Arabnia   +2 more
semanticscholar   +1 more source

Prediction of Dye Removal Using Machine Learning Techniques

Sakarya University Journal of Computer and Information Sciences
This study aims to predict the removal efficiency of methylene blue dye using experimental data collected from adsorption processes involving acorn-based biosorbents.
Dilay Bozdağ Ak, İhsan Hakan Selvi
doaj   +1 more source

Entity Personalized Talent Search Models with Tree Interaction Features

, 2019
Talent Search systems aim to recommend potential candidates who are a good match to the hiring needs of a recruiter expressed in terms of the recruiter's search query or job posting.
Buchanan, Erik, Geyik, Sahin, Ma, Yiming, Ozcaglar, Cagri, Schmitz, Brian, Sharma, Prakhar, Shelkovnykov, Alex   +6 more
core   +1 more source

Frugal Optimization for Cost-related Hyperparameters

, 2020
The increasing demand for democratizing machine learning algorithms calls for hyperparameter optimization (HPO) solutions at low cost. Many machine learning algorithms have hyperparameters which can cause a large variation in the training cost.
Huang, Silu, Wang, Chi, Wu, Qingyun
core   +2 more sources

THE EFFECT OF SAMPLE SIZE ON THE STABILITY OF XGBOOST MODEL PERFORMANCE IN PREDICTING STUDENT STUDY PERIOD

Barekeng
Student success can be defined based on the period of study taken until graduation from college. Machine learning can be used to predict the factors that are thought to influence student success.
Muhammad Lintang Damar Sakti, Jailani Jailani, Heri Retnawati, Kana Hidayati, Nur Hadi Waryanto, Zulfa Safina Ibrahim, Asma’ Khoirunnisa, Firdaus Amruzain Satiranandi Wibowo, Miftah Okta Berlian, Angella Ananta Batubara   +9 more
doaj   +1 more source

One method of generating synthetic data to assess the upper limit of machine learning algorithms performance

Cogent Engineering, 2020
Based on statistics from the World Nuclear Association, Kazakhstan has the highest uranium production in the world. Most of the uranium in the country is mined via in-situ leaching and the accurate classification of lithologic composition using electric ...
Yan I. Kuchin, Ravil I. Mukhamediev, Kirill O. Yakunin   +2 more
doaj   +1 more source

Cryptocurrency Price Prediction Using Enhanced PSO with Extreme Gradient Boosting Algorithm

Cybernetics and Information Technologies, 2023
Due to the highly volatile tendency of Bitcoin, there is a necessity for a better price prediction model. Only a few researchers have focused on the feasibility to apply various modelling approaches.
Srivastava Vibha, Dwivedi Vijay Kumar, Singh Ashutosh Kumar   +2 more
doaj   +1 more source

Accurate ADMET Prediction with XGBoost

, 2022
The absorption, distribution, metabolism, excretion, and toxicity (ADMET) properties are important in drug discovery as they define efficacy and safety. In this work, we applied an ensemble of features, including fingerprints and descriptors, and a tree-based machine learning model, extreme gradient boosting, for accurate ADMET prediction.
Tian, Hao, Ketkar, Rajas, Tao, Peng
openaire   +2 more sources

Global Burden of Iodine Deficiency: Insights and Projections to 2050 Using XGBoost and SHAP

Advances in Nutrition
Iodine deficiency (ID) poses a significant global public health challenge. This study aimed to analyze trends from 1990 to 2021 and project future patterns ≤2050 using the extreme gradient boosting (XGBoost) model, with Shapley additive explanations ...
Dan Liang, Li Wang, Panpan Zhong, Jiuxiu Lin, Leyan Chen, Qifan Chen, Shuang Liu, Zhen Luo, Changwen Ke, Ying-hau Lai   +9 more
semanticscholar   +1 more source