Suchergebnisse - "regression tree algorithms"

Stratifying Mortality Risk in Intensive Care: A Comprehensive Analysis Using Cluster Analysis and Classification and Regression Tree Algorithms

Autoren: Antonio Romanelli Salvatore Palmese Serena De Vita et al.

Quelle: Intensive Care Research, Vol 4, Iss 2, Pp 116-128 (2024)

Schlagwörter: Classification and regression tree, RC86-88.9, Medical emergencies. Critical care. Intensive care. First aid, 01 natural sciences, 3. Good health, Sequential Organ Failure Assessment, 03 medical and health sciences, Cluster analysis, 0302 clinical medicine, Medicine, Mortality, 0101 mathematics, Charlson Comorbidity Index, Simplified Acute Physiology Score II

Zugangs-URL: https://doaj.org/article/4993a22ae25a4284950bf61b9b4203a5

A Comparative Study of Linear Regression and Regression Tree Algorithms to Determine Reservoir Water Saturation

Autoren: Amad Hussen

Retracted: A Smart of Classification and Regression Tree Algorithms for Detection of Land Cover from Hyper Spectral Data

Autoren: Chetan Chaudhary Shiv Shankar Shankar C Menaka

Quelle: 2024 International Conference on Optimization Computing and Wireless Communication (ICOCWC). :1-7

Using Different Regression Tree Algorithms to Predict Soil Organic Matter with Digital Color Parameters in Soil Profile Wall

Autoren: Gafur GÖZÜKARA Yasin ALTAY

Quelle: Volume: 7, Issue: 2 326-336
Uluslararası Tarım ve Yaban Hayatı Bilimleri Dergisi
International Journal of Agricultural and Wildlife Sciences

Schlagwörter: 2. Zero hunger, 13. Climate action, Data mining algoritms, interpolations, pasture soils, CIE Lab, soil color, Veri madenciliği algoritmaları, interpolasyon, mera toprakları, toprak rengi, Soil Sciences and Ecology, 0401 agriculture, forestry, and fisheries, Toprak Bilimi ve Ekolojisi, 04 agricultural and veterinary sciences, 15. Life on land, 6. Clean water, 12. Responsible consumption

Dateibeschreibung: application/pdf

Zugangs-URL: https://dergipark.org.tr/en/download/article-file/1674715
https://avesis.ogu.edu.tr/yayin/b0f14cb2-dd89-49be-b492-6e2cd9f531cf/using-different-regression-tree-algorithms-to-predict-soil-organic-matter-with-digital-color-parameters-in-soil-profile-wall
https://dergipark.org.tr/en/doi/10.24180/ijaws.907028
https://dergipark.org.tr/tr/download/article-file/1674715
https://dergipark.org.tr/tr/pub/ijaws/issue/64486/907028

GIS-based landslide susceptibility mapping using numerical risk factor bivariate model and its ensemble with linear multivariate regression and boosted regression tree algorithms

Autoren: Khalil Rezaei Alireza Arabameri Biswajeet Pradhan et al.

Quelle: Journal of Mountain Science. 16:595-618

Schlagwörter: 13. Climate action, 15. Life on land, 01 natural sciences, 0105 earth and related environmental sciences

Zugangs-URL: https://link.springer.com/article/10.1007/s11629-018-5168-y

Retraction Notice: A Smart of Classification and Regression Tree Algorithms for Detection of Land Cover from Hyper Spectral Data

Autoren: Chetan Chaudhary Shiv Shankar Shankar C Menaka

Quelle: 2024 International Conference on Optimization Computing and Wireless Communication (ICOCWC). :1-1

A Short-Term Forecasting of Wind Power Outputs Based on Gradient Boosting Regression Tree Algorithms

Autoren: Soyoung Park Solyoung Jung Jaegul Lee et al.

Quelle: Energies, Vol 16, Iss 3, p 1132 (2023)

Schlagwörter: renewable energy, wind-power forecasting, machine learning, gradient-boosting machine (GBM), Technology

Dateibeschreibung: electronic resource

Relation: https://www.mdpi.com/1996-1073/16/3/1132; https://doaj.org/toc/1996-1073

Zugangs-URL: https://doaj.org/article/db15470c9bfe45f1a2611a9768af8d62

GIS-based landslide susceptibility mapping using numerical risk factor bivariate model and its ensemble with linear multivariate regression and boosted regression tree algorithms

Autoren: Arabameri, A. Pradhan, B. Rezaei, K. et al.

Index Begriffe: Engineering and Technology, Teknik och teknologier, Article in journal, info:eu-repo/semantics/article, text

URL: http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-288316
Journal of Mountain Science, 1672-6316, 2019, 16:3, s. 595-618

GIS-based landslide susceptibility mapping using numerical risk factor bivariate model and its ensemble with linear multivariate regression and boosted regression tree algorithms

Autoren: Arabameri, A Pradhan, B Rezaei, K et al.

Index Begriffe: Journal Article

URL: http://hdl.handle.net/10453/135376
Journal of Mountain Science
10.1007/s11629-018-5168-y

Mothers Matter: Using Regression Tree Algorithms to Predict Adolescents’ Sharing of Drunk References on Social Media

Autoren: Kurten, Sebastian Winant, David Beullens, Kathleen

Quelle: Int J Environ Res Public Health
International Journal of Environmental Research and Public Health
Volume 18
Issue 21

Schlagwörter: Male, Adolescent, Alcohol Drinking, social media, WILLINGNESS, Mothers, Environmental Sciences & Ecology, Toxicology, Article, NETWORKING SITES, ALCOHOL-USE, 0508 media and communications, 5. Gender equality, BINGE-DRINKING, Social Norms, CART, Humans, adolescents, Public, Environmental & Occupational Health, COMPARISON ORIENTATION, RISK, Science & Technology, 05 social sciences, PERFORMANCE, PARENTAL SOCIALIZATION, 3. Good health, machine learning, Cross-Sectional Studies, RELIABILITY, extreme gradient boosting, regression tree, Female, Life Sciences & Biomedicine, Social Media, Environmental Sciences, PEER NORMS, Algorithms

Dateibeschreibung: application/pdf

Zugangs-URL: https://www.mdpi.com/1660-4601/18/21/11338/pdf
https://pubmed.ncbi.nlm.nih.gov/34769854
https://www.mdpi.com/1660-4601/18/21/11338/pdf
https://www.mdpi.com/1660-4601/18/21/11338
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8583103
https://europepmc.org/article/MED/34769854
https://lirias.kuleuven.be/handle/123456789/683170
https://doi.org/10.3390/ijerph182111338

Establishment of the Model for Estimating the Organic Carbon Content of Forest Topsoil Based on Remote Sensing Data

Autoren: Shulin Zheng Jie Zhang Mingyue Song et al.

Quelle: IEEE Access, Vol 12, Pp 162062-162074 (2024)

Schlagwörter: remote sensing data, linear regression algorithms, Topsoil organic carbon content, Electrical engineering. Electronics. Nuclear engineering, regression tree algorithms, TK1-9971

Zugangs-URL: https://doaj.org/article/5459c55b93254ff889db8e4281003f52

Stratifying Mortality Risk in Intensive Care: A Comprehensive Analysis Using Cluster Analysis and Classification and Regression Tree Algorithms.

Autoren: Romanelli, Antonio Palmese, Salvatore De Vita, Serena et al.

Quelle: Intensive Care Research; Jun2024, Vol. 4 Issue 2, p116-128, 13p

Schlagwörter: MORTALITY, CRITICAL care medicine, MACHINE learning, DECISION making, REGRESSION trees

A Short-Term Forecasting of Wind Power Outputs Based on Gradient Boosting Regression Tree Algorithms.

Autoren: Park, Soyoung Jung, Solyoung Lee, Jaegul et al.

Quelle: Energies (19961073); Feb2023, Vol. 16 Issue 3, p1132, 12p

Schlagwörter: WIND power, WIND forecasting, REGRESSION trees, ELECTRIC power distribution grids, LOAD forecasting (Electric power systems), WIND power plants, MACHINE learning, FORECASTING

Geografische Kategorien: CHEJU Island (Korea)

GIS-based landslide susceptibility mapping using numerical risk factor bivariate model and its ensemble with linear multivariate regression and boosted regression tree algorithms

Autoren: Arabameri, Alireza Pradhan, Biswajeet Rezaei, Khalil et al.

Schlagwörter: Landslide susceptibility, GIS, Remote sensing, Bivariate model, Multivariate model, Machine learning model, manag, geo

Relation: http://ir.imde.ac.cn/handle/131551/46454

Verfügbarkeit: http://ir.imde.ac.cn/handle/131551/46454

Leveraging mixed-effects regression trees for the analysis of high-dimensional longitudinal data to identify the low and high-risk subgroups: simulation study with application to genetic study.

Autoren: Jahangiri, Mina Kazemnejad, Anoshirvan Goldfeld, Keith S. et al.

Quelle: BioData Mining; 3/19/2025, Vol. 18 Issue 1, p1-18, 18p

Schlagwörter: GENETIC profile, SINGLE nucleotide polymorphisms, AUTOREGRESSIVE models, INDEPENDENT variables, BODY mass index, REGRESSION trees

An Exact Least Trimmed Squares Algorithm for a Range of Coverage Values

Autoren: Hofmann, Marc H. Gatu, Cristian Kontoghiorghes, Erricos John

Quelle: Journal of Computational and Graphical Statistics. 19:191-204

Schlagwörter: Regression tree algorithms, Robust estimation, SOCIAL SCIENCES, QR factorization, Outliers, Social Sciences, 0101 mathematics, 01 natural sciences

Dateibeschreibung: pdf

Zugangs-URL: https://www.tandfonline.com/doi/abs/10.1198/jcgs.2009.07091
https://amstat.tandfonline.com/doi/abs/10.1198/jcgs.2009.07091
https://hdl.handle.net/20.500.14279/1976

Characterizing fire history on military land using machine learning and landsat imagery.

Autoren: O'Grady, Maura C. Wells, Adam G. Just, Michael G. et al.

Quelle: International Journal of Wildland Fire; 2025, Vol. 34 Issue 8, p1-13, 13p

Schlagwörter: WILDFIRES, MILITARY bases, RANDOM forest algorithms, MACHINE learning, REMOTE-sensing images, REGRESSION trees, FIRE management

Geografische Kategorien: UNITED States

Firma/Körperschaft: UNITED States. Army

Risk stratification of AUC upward deviation in patients with low serum creatinine levels treated with vancomycin: a multicenter retrospective study Open Access.

Autoren: Ishigo, Tomoyuki Suzuki, Ayako Ibe, Yuta et al.

Quelle: Journal of Pharmacy & Pharmacology. Sep2025, Vol. 77 Issue 9, p1255-1263. 9p.

Schlagwörter: *VANCOMYCIN, *CREATININE, *RISK assessment, *PHARMACOKINETICS, *KIDNEY physiology, *RETROSPECTIVE studies, *DRUG monitoring, *MEDICAL research

A comparative evaluation of the enhanced PLS‐Tree algorithm with multiple latent score vectors.

Autoren: Panjwani, Shyam Almazan, Alice Wei, Hao et al.

Quelle: Journal of Advanced Manufacturing & Processing; Jul2025, Vol. 7 Issue 3, p1-10, 10p

Schlagwörter: MULTICOLLINEARITY, HETEROGENEITY, CHEMICAL process industries, PARTIAL least squares regression, MACHINE learning, DATA analysis, FORECASTING

Effect of Texture Feature Distribution on Agriculture Field Type Classification with Multitemporal UAV RGB Images.

Autoren: Lee, Chun-Han Chen, Kuang-Yu Liu, Li-yu Daisy

Quelle: Remote Sensing; Apr2024, Vol. 16 Issue 7, p1221, 19p

Schlagwörter: CART algorithms, LANDSAT satellites, IMAGE recognition (Computer vision), PRODUCTION management (Manufacturing), SUPPORT vector machines, CLASSIFICATION

Geografische Kategorien: TAIWAN