Results 251 to 260 of about 91,735 (266)

XGBoost-Based Android Malware Detection

2017 13th International Conference on Computational Intelligence and Security (CIS), 2017
Malware remains the most significant security threat to smartphones in spite of the constantly upgrading of the system. In this paper, we introduce an Android malware detection method based on XGBoost model. We subsequently discuss the effect of feature selection on the classification.
Jiong Wang, Boquan Li, Yuwei Zeng
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XGboost Algoritması

Aşırı Gradyan Artırma Algoritması, kısa adıyla “XGBoost” (Extreme Gradient Boosting Algorithm), Karar Ağaçlarının (KA) özelleştirilmiş bir formu olup sınıflandırma, tahmin ve sıralama yöntemi olarak literatürde ön plana çıkmaktadır. 2015 Bilgi Keşfi ve Veri Madenciliği (Knowledge Discovery and Data Mining-KDD) kupasında seçilen en iyi 10 çözümün ...
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Predict credit risk with XGBoost

Applied and Computational Engineering
The risk of credit loan exists when the bank issues a loan to the borrower, because the borrower has no way to repay the amount or defaults, which exposes the financial institution to the risk of loss. This causes financial institutions to suffer from effects that affect their creditworthiness, loss of capital and increased management and collection of
Wenhao Wang, Xiyi Zuo, Dantong Han
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Improving XGBoost with Imagination Sampling

Communications of the Blyth Institute, 2020
Imagination Sampling is the usage of a person as an oracle for generating or improving machine learning models. Previous work demonstrated a general system for using Imagination Sampling for obtaining multibox models. Here, the possibility of importing such models as the starting point for further automatic enhancement is explored.
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Road Accident Prediction Using Xgboost

2022 International Conference on Emerging Techniques in Computational Intelligence (ICETCI), 2022
Katha Mehta, Shagun Jain, Amisha Agarwal, Archana Bomnale   +3 more
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Bird Apprehension Forecasting with XGBoost

Anais do Computer on the Beach
ABSTRACTThis article applied exploratory data analysis (EDA) and time seriesforecasting using extreme gradient boosting (XGBoost) to birdapprehension data from the Brazilian Institute of Environmentand Renewable Natural Resources (IBAMA) covering 2010 to 2024,the dataset processed included 150,000 records, filtered to focuson significant patterns ...
Fabrício Pereira Diniz, José Luis Seixas Junior, Guilherme Henrique de Souza Nakahata   +2 more
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Heart Disease Prediction Using XGBoost

2022 Third International Conference on Intelligent Computing Instrumentation and Control Technologies (ICICICT), 2022
Srichand Doki, Siddhartha Devella, Sumanth Tallam, Sai Sujeeth Reddy Gangannagari, P. Sampathkrishna Reddy, G. Pradeep Reddy   +5 more
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Scalable and Secure Federated XGBoost

ICASSP 2023 - 2023 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2023
Quang Minh Nguyen, Nhan Khanh Le, Lam M. Nguyen   +2 more
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Network Intrusion Detection with XGBoost

2020
Arnaldo Gouveia, Miguel Correia
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Adaptive Fast XGBoost for Regression

2022
Fernanda Maria de Souza, Julia Grando, Fabiano Baldo   +2 more
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