Results 41 to 50 of about 139,430 (360)

Comparative Analysis of Feature Selection Methods with XGBoost for Malware Detection on the Drebin Dataset

Jurnal Sisfokom
Malware, or malicious software, continues to evolve alongside increasing cyberattacks targeting individual devices and critical infrastructure. Traditional detection methods, such as signature-based detection, are often ineffective against new or ...
Ines Aulia Latifah, Fauzi Adi Rafrastara, Jevan Bintoro, Wildanil Ghozi, Waleed Mahgoub Osman   +4 more
doaj   +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

XGBoost-enhanced ensemble model using discriminative hybrid features for the prediction of sumoylation sites

BioData Mining
Posttranslational modifications (PTMs) are essential for regulating protein localization and stability, significantly affecting gene expression, biological functions, and genome replication.
Salman Khan, Sumaiya Noor, Tahir Javed, Afshan Naseem, Fahad Aslam, Salman A. Alqahtani, Nijad Ahmad   +6 more
semanticscholar   +1 more source

Predicting Antibiotic Resistance in ICUs Patients by Applying Machine Learning in Vietnam

Infection and Drug Resistance, 2023
Viet Tran Quoc,1 Dung Nguyen Thi Ngoc,2,3 Trung Nguyen Hoang,4 Hoa Vu Thi,4 Minh Tong Duc,4 Thanh Do Pham Nguyet,2 Thanh Nguyen Van,5 Diep Ho Ngoc,2 Giang Vu Son,6 Thanh Bui Duc7 1Intensive Care Unit, Military Hospital 175, Ho Chi Minh City, Vietnam ...
Tran Quoc V, Nguyen Thi Ngoc D, Nguyen Hoang T, Vu Thi H, Tong Duc M, Do Pham Nguyet T, Nguyen Van T, Ho Ngoc D, Vu Son G, Bui Duc T   +9 more
doaj  

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

Interpretable Machine Learning with SHAP and XGBoost for Lung Cancer Prediction Insights

Journal of Applied Informatics and Computing
Kanker paru-paru tetap menjadi salah satu penyebab kematian utama di seluruh dunia, dan deteksi dini melalui metode yang akurat dan andal sangat penting untuk meningkatkan prognosis pasien.
Taufik Kurniawan, Laily Hermawanti, Achmad Nuruddin Safriandono   +2 more
doaj   +1 more source

Induction of Non-Monotonic Logic Programs to Explain Boosted Tree Models Using LIME

, 2018
We present a heuristic based algorithm to induce \textit{nonmonotonic} logic programs that will explain the behavior of XGBoost trained classifiers.
Gupta, Gopal, Shakerin, Farhad
core   +1 more source

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

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   +1 more source

Tumor mutational burden as a determinant of metastatic dissemination patterns

Molecular Oncology, EarlyView.
This study performed a comprehensive analysis of genomic data to elucidate whether metastasis in certain organs share genetic characteristics regardless of cancer type. No robust mutational patterns were identified across different metastatic locations and cancer types.
Eduardo Candeal, Andrea Moreno‐Manuel, Miguel Salvadó‐Pertierra, Cristina Santos‐Vivas, Rebeca Sanz‐Pamplona   +4 more
wiley   +1 more source

Makine Öğrenmesi Yaklaşımı Kullanılarak Tavuk Etinden İzole Edilen Listeria’ya Karşı Ozonun Antibakteriyel Etkisinin Tahmin Edilmesi

Turkish Journal of Agriculture: Food Science and Technology
Bu çalışmada, ozon gazının Listeria spp. (tavuk işletmeleri ve tavuk etlerinden izole edilen) üzerine antibakteriyel etkilerini tahmin etmek amacıyla %99.99 doğruluk oranına sahip bir XGBoost tabanlı tahmin modeli geliştirilmiştir. Makine öğrenimi süreci
Bülent Zorlugenç, Sema Atasever, Feyza Kıroğlu Zorlugenç   +2 more
doaj   +1 more source