Results 21 to 30 of about 95,729 (269)
CLASSIFICATION OF STUDENT GRADUATION STATUS USING XGBOOST ALGORITHM
Barekeng, 2023 College is an optional final stage in formal education. At this time, universities are required to have good quality by utilizing all the resources they have. Therefore, efforts are needed to help the faculty and study program make policies and decisions.
Maria Welita Dwinanda +2 more
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Predicting rental listing popularity : 2 Sigma connect Renthop [PDF]
, 2017 Renting a perfect apartment can be a hassle. There are plenty of features people care about when it comes to finding the apartment, such as price, hardwood floor, dog park, laundry room, etc.
Cai, Shiyao
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Sustainable Investing and the Cross-Section of Maximum Drawdown [PDF]
, 2019 We use supervised learning to identify factors that predict the cross-section of maximum drawdown for stocks in the US equity market. Our data run from January 1980 to June 2018 and our analysis includes ordinary least squares, penalized linear ...
Goldberg, Lisa R., Mouti, Saad
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Learning to Tune XGBoost with XGBoost
, 2019 In this short paper we investigate whether meta-learning techniques can be used to more effectively tune the hyperparameters of machine learning models using successive halving (SH). We propose a novel variant of the SH algorithm (MeSH), that uses meta-regressors to determine which candidate configurations should be eliminated at each round.
Sommer, Johanna +2 more
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, 2021 The XGBoost method has many advantages and is especially suitable for statistical analysis of big data, but its loss function is limited to convex functions. In many specific applications, a nonconvex loss function would be preferable. In this paper, I propose a generalized XGBoost method, which requires weaker loss function constraint and involves ...
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Feature Interactions in XGBoost
, 2020 In this paper, we investigate how feature interactions can be identified to be used as constraints in the gradient boosting tree models using XGBoost's implementation. Our results show that accurate identification of these constraints can help improve the performance of baseline XGBoost model significantly.
Goyal, Kshitij +2 more
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Privacy-Preserving XGBoost Inference
, 2020 Although machine learning (ML) is widely used for predictive tasks, there are important scenarios in which ML cannot be used or at least cannot achieve its full potential. A major barrier to adoption is the sensitive nature of predictive queries. Individual users may lack sufficiently rich datasets to train accurate models locally but also be unwilling
Meng, Xianrui, Feigenbaum, Joan
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Journal of Multidisciplinary Healthcare, 2023 Shan Yang,1 Lirui Cao,2 Yongfang Zhou,3 Chenggong Hu1 1Department of Critical Care Medicine, West China Hospital of Sichuan University, Chengdu, Sichuan, 610041, People’s Republic of China; 2West China Hospital of Sichuan University, Chengdu, Sichuan ...
Yang S, Cao L, Zhou Y, Hu C
doaj
Jambura Journal of MathematicsMachine learning classification is an effective tool for categorizing data based on patterns, which is particularly useful in analyzing the Human Development Index (HDI) in Indonesia. HDI serves as a key indicator of regional development progress, making
Yunna Mentari Indah +4 more
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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 +6 more
core +2 more sources