Suchergebnisse - "Extreme gradient boosting algorithm"

Aircraft flight quality evaluation based on grey correlation analysis and XGBoost

Autoren: SUN Baosong SHI Zhiguo PAN Xinlong et al.

Quelle: Hangkong gongcheng jinzhan, Vol 16, Iss 4, Pp 74-81 (2025)

Schlagwörter: grey correlation analysis method, quality assessment model, xgboost（extreme gradient boosting） algorithm, machine learning, Motor vehicles. Aeronautics. Astronautics, TL1-4050

Dateibeschreibung: electronic resource

Relation: http://hkgcjz.cnjournals.com/hkgcjz/article/abstract/2024060; https://doaj.org/toc/1674-8190

Zugangs-URL: https://doaj.org/article/61892dc1cab14f76a6bc30ce6a687031

A Decision Support System For Early Stage Parkinson's Diagnosis from EEG Data Using Symbolic Mutual Information and KAC Features

Autoren: Neslihan Baki Nurhan Gürsel Özmen

Quelle: Sakarya Üniversitesi Fen Bilimleri Enstitüsü Dergisi, Vol 28, Iss 5, Pp 912-923 (2024)

Schlagwörter: weighted symbolic mutual information (wsmi), Chemistry, parkinson, extreme gradient boosting algorithm, TA1-2040, kolmogorov algorithmic complexity (kac), Engineering (General). Civil engineering (General), QD1-999, electroencephalography

Zugangs-URL: https://doaj.org/article/82f2d11f55af4e7e9cd6d659a5932f62

Decoding the synergy: unveiling gradient boosting regression model for multivariate quantitation of pioglitazone, alogliptin and glimepiride in pure and tablet dosage forms

Autoren: Mahmoud M. Elkhoudary Aya A. Marie Sherin F. Hammad et al.

Quelle: BMC Chemistry, Vol 18, Iss 1, Pp 1-13 (2024)

Schlagwörter: Partial least squares, UV/Vis spectroscopy, Artificial neural networks, Extreme gradient boosting algorithm, Support vector regression, Chemistry, QD1-999

Dateibeschreibung: electronic resource

Relation: https://doaj.org/toc/2661-801X

Zugangs-URL: https://doaj.org/article/9f1c1343a9e74c53b0b827fd99b2c718

A Novel SHAP-GAN Network for Interpretable Ovarian Cancer Diagnosis

Autoren: Jingxun Cai Zne-Jung Lee Zhihxian Lin et al.

Quelle: Mathematics ; Volume 13 ; Issue 5 ; Pages: 882

Schlagwörter: ovarian cancer, feature selection, extreme gradient boosting algorithm, generative adversarial networks, SHAP

Dateibeschreibung: application/pdf

Relation: E2: Control Theory and Mechanics; https://dx.doi.org/10.3390/math13050882

Verfügbarkeit: https://doi.org/10.3390/math13050882

An integrated cloud system based serverless android app for generalised tractor drawbar pull prediction model using machine learning

Autoren: Harsh Nagar Rajendra Machavaram Ambuj et al.

Quelle: Systems Science & Control Engineering, Vol 12, Iss 1 (2024)

Schlagwörter: Tractor drawbar pull prediction, generalised model, machine learning, extreme gradient boosting algorithm, cloud-based serverless android app, Control engineering systems. Automatic machinery (General), TJ212-225, Systems engineering, TA168

Dateibeschreibung: electronic resource

Relation: https://doaj.org/toc/2164-2583

Zugangs-URL: https://doaj.org/article/c0a3baaad9104e48af44c4e409709736

Comparison of Two Methods, Gradient Boosting and Extreme Gradient Boosting to Pre- dict Survival in Covid-19 Data

Autoren: Nadiasadat Taghavi Razavizadeh Maryam Salari Mostafa Jafari et al.

Quelle: Journal of Biostatistics and Epidemiology, Vol 9, Iss 3 (2023)

Schlagwörter: Gradient boosting algorithm, Extreme gradient boosting algorithm, survival analysis, Covid-19, QH301-705.5, Biology (General), Probabilities. Mathematical statistics, QA273-280, 3. Good health

Zugangs-URL: https://doaj.org/article/101467ecd14a4b9b9d357098a75c8465

Optimizing a Machine Learning Algorithm by a Novel Metaheuristic Approach: A Case Study in Forecasting

Autoren: Bahadır Gülsün Muhammed Resul Aydin

Quelle: Mathematics, Vol 12, Iss 24, p 3921 (2024)

Schlagwörter: extreme gradient boosting algorithm, machine learning algorithm, forecasting model, metaheuristic algorithms, hyperparameter tuning, hybrid metaheuristic, Mathematics, QA1-939

Dateibeschreibung: electronic resource

Relation: https://www.mdpi.com/2227-7390/12/24/3921; https://doaj.org/toc/2227-7390

Zugangs-URL: https://doaj.org/article/67a199666ceb44b891e3c76e982cc35d

Prediction of Ionospheric Scintillations Using Machine Learning Techniques during Solar Cycle 24 across the Equatorial Anomaly

Autoren: Sebwato Nasurudiin Akimasa Yoshikawa Ahmed Elsaid et al.

Quelle: Atmosphere, Vol 15, Iss 10, p 1213 (2024)

Schlagwörter: machine learning, ensemble learning techniques, ionospheric scintillation, Random Forest algorithm, eXtreme Gradient Boosting algorithm, Meteorology. Climatology, QC851-999

Dateibeschreibung: electronic resource

Relation: https://www.mdpi.com/2073-4433/15/10/1213; https://doaj.org/toc/2073-4433

Zugangs-URL: https://doaj.org/article/53585aa945f24ddd9c00666ee670140f

Early prediction of battery degradation in grid-scale battery energy storage system using extreme gradient boosting algorithm

Autoren: Chico Hermanu Brillianto Apribowo Sasongko Pramono Hadi Franscisco Danang Wijaya et al.

Quelle: Results in Engineering, Vol 21, Iss , Pp 101709- (2024)

Schlagwörter: Battery energy storage system, Battery degradation, Remaining useful life, Extreme gradient boosting algorithm, Hyperparameter tuning, Technology

Dateibeschreibung: electronic resource

Relation: http://www.sciencedirect.com/science/article/pii/S2590123023008368; https://doaj.org/toc/2590-1230

Zugangs-URL: https://doaj.org/article/81be6e336e14402c80fb86221fe34894

A Sustainable Approach to Asthma Diagnosis: Classification with Data Augmentation, Feature Selection, and Boosting Algorithm

Autoren: Zne-Jung Lee Ming-Ren Yang Bor-Jiunn Hwang

Quelle: Diagnostics, Vol 14, Iss 7, p 723 (2024)

Schlagwörter: asthma, data augmentation, feature selection, extreme gradient boosting algorithm, generative adversarial networks, Medicine (General), R5-920

Relation: https://www.mdpi.com/2075-4418/14/7/723; https://doaj.org/toc/2075-4418; https://doaj.org/article/c34471b39ca14d3da31ed60fc7fb2f4c

Verfügbarkeit: https://doi.org/10.3390/diagnostics14070723
https://doaj.org/article/c34471b39ca14d3da31ed60fc7fb2f4c

A Haze Feature Extraction and Pollution Level Identification Pre-warning Algorithm

Autoren: Zhang, Y Ma, J Hu, L et al.

Weitere Verfasser: Zhang, Y Ma, J Hu, L et al.

Quelle: Computers, Materials & Continua. 64:1929-1944

Schlagwörter: feature extraction, deep belief networks, Haze pollution, PM2.5, 02 engineering and technology, 01 natural sciences, Extreme gradient boosting algorithm, eXtreme gradient boosting algorithm, 13. Climate action, 0202 electrical engineering, electronic engineering, information engineering, Feature extraction, Deep belief networks, haze pollution, 0105 earth and related environmental sciences

Dateibeschreibung: Print-Electronic

Zugangs-URL: http://www.techscience.com/cmc/v64n3/39468/pdf
https://bura.brunel.ac.uk/bitstream/2438/22730/1/FullText.pdf
https://bura.brunel.ac.uk/handle/2438/22730
https://www.techscience.com/cmc/v64n3/39468/pdf
https://bura.brunel.ac.uk/handle/2438/22730

Prediction of strata behaviors law based on GRU and XGBoost

Autoren: CHAI Jing LIU Yilong WANG Anyi et al.

Quelle: Gong-kuang zidonghua, Vol 48, Iss 1, Pp 91-97 (2022)

Schlagwörter: strata behaviors law, extreme gradient boosting algorithm, xgboost, gru, optical fiber frequency shift value, optical fiber average frequency shift change, Mining engineering. Metallurgy, TN1-997

Dateibeschreibung: electronic resource

Relation: https://doaj.org/toc/1671-251X

Zugangs-URL: https://doaj.org/article/16c0494d38f14bf2bda16f7938cc908c

Machine learning-aided risk stratification in Philadelphia chromosome-positive acute lymphoblastic leukemia

Autoren: Satoshi Nishiwaki Isamu Sugiura Daisuke Koyama et al.

Quelle: Biomarker Research, Vol 9, Iss 1, Pp 1-4 (2021)

Schlagwörter: eXtreme gradient boosting algorithm, Machine learning, Philadelphia chromosome-positive acute lymphoblastic leukemia, Prognostic factor, Survival stratification, Therapeutics. Pharmacology, RM1-950

Dateibeschreibung: electronic resource

Relation: https://doaj.org/toc/2050-7771

Zugangs-URL: https://doaj.org/article/daa0493c46a44ee9abff03074f4a1788

Hub Genes Identification, Small Molecule Compounds Prediction for Atrial Fibrillation and Diagnostic Model Construction Based on XGBoost Algorithm

Autoren: Lingzhi Yang Yunwei Chen Wei Huang

Quelle: Frontiers in Cardiovascular Medicine, Vol 9 (2022)

Schlagwörter: atrial fibrillation, Connectivity map, the eXtreme Gradient Boosting algorithm, the Sharpley Additive exPlanations, rank robust aggregation, weighted gene coexpression network analysis, Diseases of the circulatory (Cardiovascular) system, RC666-701

Dateibeschreibung: electronic resource

Relation: https://www.frontiersin.org/articles/10.3389/fcvm.2022.920399/full; https://doaj.org/toc/2297-055X

Zugangs-URL: https://doaj.org/article/f66e9a2a89684e9b874e939e32efd170

A Bus Passenger Flow Prediction Model Fused with Point-of-Interest Data Based on Extreme Gradient Boosting

Autoren: Wanjun Lv Yongbo Lv Qi Ouyang et al.

Quelle: Applied Sciences, Vol 12, Iss 940, p 940 (2022)

Schlagwörter: public transportation, passenger flow prediction, point-of-interest data, extreme gradient boosting algorithm, Technology, Engineering (General). Civil engineering (General), TA1-2040, Biology (General), QH301-705.5, Physics, QC1-999, Chemistry, QD1-999

Relation: https://www.mdpi.com/2076-3417/12/3/940; https://doaj.org/toc/2076-3417; https://doaj.org/article/27dabf885a924f348d9ac5917258eca2

Verfügbarkeit: https://doi.org/10.3390/app12030940
https://doaj.org/article/27dabf885a924f348d9ac5917258eca2

Fusing XGBoost and SHAP Models for Maritime Accident Prediction and Causality Interpretability Analysis

Autoren: Cheng Zhang Xiong Zou Chuan Lin

Quelle: Journal of Marine Science and Engineering, Vol 10, Iss 1154, p 1154 (2022)

Schlagwörter: maritime accidents, risk prediction, causal analysis, extreme gradient boosting algorithm, interpretable machine learning, Naval architecture. Shipbuilding. Marine engineering, VM1-989, Oceanography, GC1-1581

Relation: https://www.mdpi.com/2077-1312/10/8/1154; https://doaj.org/toc/2077-1312; https://doaj.org/article/3e18f1ab599c40c89b679e65df8e40dc

Verfügbarkeit: https://doi.org/10.3390/jmse10081154
https://doaj.org/article/3e18f1ab599c40c89b679e65df8e40dc

Prediction of Credit Card Defaulters Based on SMOTE-XGBoost Model

Autoren: Jin, Lingmin Wu, Zengyuan Zhao, Jiali

Quelle: WHICEB 2022 Proceedings

Schlagwörter: credit card default, unbalanced data, the Extreme Gradient Boosting algorithm(XGBoost), the Synthetic Minority Oversampling Technique (SMOTE)

Dateibeschreibung: application/pdf

Relation: https://aisel.aisnet.org/whiceb2022/64; https://aisel.aisnet.org/context/whiceb2022/article/1032/viewcontent/11.pdf

Verfügbarkeit: https://aisel.aisnet.org/whiceb2022/64
https://aisel.aisnet.org/context/whiceb2022/article/1032/viewcontent/11.pdf

Additional file 1 of Machine learning-aided risk stratification in Philadelphia chromosome-positive acute lymphoblastic leukemia

Autoren: Satoshi Nishiwaki (10166913) Isamu Sugiura (9556673) Daisuke Koyama (534725) et al.

Schlagwörter: Medicine, Cell Biology, Biotechnology, Cancer, Hematology, Biological Sciences not elsewhere classified, Mathematical Sciences not elsewhere classified, Information Systems not elsewhere classified, eXtreme gradient boosting algorithm, Machine learning, Philadelphia chromosome-positive acute lymphoblastic leukemia, Prognostic factor, Survival stratification

Relation: https://figshare.com/articles/figure/Additional_file_1_of_Machine_learning-aided_risk_stratification_in_Philadelphia_chromosome-positive_acute_lymphoblastic_leukemia/14059779

Verfügbarkeit: https://doi.org/10.6084/m9.figshare.14059779.v1

[Diagnosis of pulmonary hypertension associated with congenital heart disease based on statistical features of the second heart sound].

Autoren: Yang X Sun J Yang H et al.

Quelle: Sheng wu yi xue gong cheng xue za zhi = Journal of biomedical engineering = Shengwu yixue gongchengxue zazhi [Sheng Wu Yi Xue Gong Cheng Xue Za Zhi] 2024 Feb 25; Vol. 41 (1), pp. 41-50.

Publikationsart: English Abstract; Journal Article

Info zur Zeitschrift: Publisher: Sichuan Sheng sheng wu yi xue gong cheng xue hui Country of Publication: China NLM ID: 9426398 Publication Model: Print Cited Medium: Print ISSN: 1001-5515 (Print) Linking ISSN: 10015515 NLM ISO Abbreviation: Sheng Wu Yi Xue Gong Cheng Xue Za Zhi Subsets: MEDLINE

MeSH-Schlagworte: Heart Sounds* , Hypertension, Pulmonary*/diagnosis , Heart Defects, Congenital*/complications , Heart Defects, Congenital*/diagnosis, Humans ; Signal Processing, Computer-Assisted ; Algorithms

Utility of Machine Learning Algorithms in Predicting Preoperative Lymph Node Metastasis in Patients With Rectal Cancer Based on Three-Dimensional Endorectal Ultrasound and Clinical and Laboratory Data.

Autoren: Huang W Lin R Ke X et al.

Quelle: Journal of ultrasound in medicine : official journal of the American Institute of Ultrasound in Medicine [J Ultrasound Med] 2023 Nov; Vol. 42 (11), pp. 2615-2627. Date of Electronic Publication: 2023 Jul 04.

Publikationsart: Journal Article

Info zur Zeitschrift: Publisher: John Wiley and Sons Country of Publication: England NLM ID: 8211547 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1550-9613 (Electronic) Linking ISSN: 02784297 NLM ISO Abbreviation: J Ultrasound Med Subsets: MEDLINE

MeSH-Schlagworte: Endosonography*/methods , Rectal Neoplasms*/diagnostic imaging , Rectal Neoplasms*/surgery , Rectal Neoplasms*/pathology, Humans ; Lymphatic Metastasis/diagnostic imaging ; Models, Statistical ; Prognosis ; Neoplasm Staging ; Algorithms ; Machine Learning ; Retrospective Studies