Zeitschriftenartikel zum Thema „Partial Dependence Plot“
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Yan, Miaomiao, und Yindong Shen. „Traffic Accident Severity Prediction Based on Random Forest“. Sustainability 14, Nr. 3 (02.02.2022): 1729. http://dx.doi.org/10.3390/su14031729.
Der volle Inhalt der QuelleDewan, Isha, und Subhash Kochar. „SOME NEW APPLICATIONS OF P–P PLOTS“. Probability in the Engineering and Informational Sciences 27, Nr. 3 (28.03.2013): 353–66. http://dx.doi.org/10.1017/s0269964813000077.
Der volle Inhalt der QuelleLee, Changro. „Training and Interpreting Machine Learning Models: Application in Property Tax Assessment“. Real Estate Management and Valuation 30, Nr. 1 (01.03.2022): 13–22. http://dx.doi.org/10.2478/remav-2022-0002.
Der volle Inhalt der QuelleFu, Xiao. „The D e (T, t) plot: A straightforward self-diagnose tool for post-IR IRSL dating procedures“. Geochronometria 41, Nr. 4 (01.12.2014): 315–26. http://dx.doi.org/10.2478/s13386-013-0167-9.
Der volle Inhalt der QuelleTran, Van Quan. „Predicting and Investigating the Permeability Coefficient of Soil with Aided Single Machine Learning Algorithm“. Complexity 2022 (25.09.2022): 1–18. http://dx.doi.org/10.1155/2022/8089428.
Der volle Inhalt der QuelleWu, Zihao, Yiyun Chen, Yuanli Zhu, Xiangyang Feng, Jianxiong Ou, Guie Li, Zhaomin Tong und Qingwu Yan. „Mapping Soil Organic Carbon in Floodplain Farmland: Implications of Effective Range of Environmental Variables“. Land 12, Nr. 6 (08.06.2023): 1198. http://dx.doi.org/10.3390/land12061198.
Der volle Inhalt der QuellePatterson, L. D., und G. Blouin-Demers. „Partial support for food availability and thermal quality as drivers of density and area used in Yarrow’s Spiny Lizards (Sceloporus jarrovii)“. Canadian Journal of Zoology 98, Nr. 2 (Februar 2020): 105–16. http://dx.doi.org/10.1139/cjz-2019-0166.
Der volle Inhalt der QuelleKhoerunnisa, Fitri, Aaron Morelos-Gomez, Hideki Tanaka, Toshihiko Fujimori, Daiki Minami, Radovan Kukobat, Takuya Hayashi et al. „Metal–semiconductor transition like behavior of naphthalene-doped single wall carbon nanotube bundles“. Faraday Discuss. 173 (2014): 145–56. http://dx.doi.org/10.1039/c4fd00119b.
Der volle Inhalt der QuelleChang, Shih-Chieh, Chan-Lin Chu, Chih-Kuang Chen, Hsiang-Ning Chang, Alice M. K. Wong, Yueh-Peng Chen und Yu-Cheng Pei. „The Comparison and Interpretation of Machine-Learning Models in Post-Stroke Functional Outcome Prediction“. Diagnostics 11, Nr. 10 (28.09.2021): 1784. http://dx.doi.org/10.3390/diagnostics11101784.
Der volle Inhalt der QuelleShiroyama, Risa, Manna Wang und Chihiro Yoshimura. „Effect of sample size on habitat suitability estimation using random forests: a case of bluegill, Lepomis macrochirus“. Annales de Limnologie - International Journal of Limnology 56 (2020): 13. http://dx.doi.org/10.1051/limn/2020010.
Der volle Inhalt der QuelleLin, Ming-Yen, Yuan-Ming Chang, Chi-Chun Li und Wen-Cheng Chao. „Explainable Machine Learning to Predict Successful Weaning of Mechanical Ventilation in Critically Ill Patients Requiring Hemodialysis“. Healthcare 11, Nr. 6 (21.03.2023): 910. http://dx.doi.org/10.3390/healthcare11060910.
Der volle Inhalt der QuelleNúñez, Jorge, Catalina B. Cortés und Marjorie A. Yáñez. „Explainable Artificial Intelligence in Hydrology: Interpreting Black-Box Snowmelt-Driven Streamflow Predictions in an Arid Andean Basin of North-Central Chile“. Water 15, Nr. 19 (26.09.2023): 3369. http://dx.doi.org/10.3390/w15193369.
Der volle Inhalt der QuelleTran, Anh-Tuan, Thanh-Hai Le und Huu May Nguyen. „Forecast of surface chloride concentration of concrete utilizing ensemble decision tree boosted“. Journal of Science and Transport Technology 2, Nr. 1 (25.03.2022): 44–56. http://dx.doi.org/10.58845/jstt.utt.2022.en57.
Der volle Inhalt der QuelleJung, Jinwoo, Jihwan Kim und Changha Jin. „DOES MACHINE LEARNING PREDICTION DAMPEN THE INFORMATION ASYMMETRY FOR NON-LOCAL INVESTORS?“ International Journal of Strategic Property Management 26, Nr. 5 (14.11.2022): 345–61. http://dx.doi.org/10.3846/ijspm.2022.17590.
Der volle Inhalt der QuelleTran, Anh-Tuan, Thanh-Hai Le und Huu May Nguyen. „Forecast of surface chloride concentration of concrete utilizing ensemble decision tree boosted“. Journal of Science and Transport Technology 2, Nr. 1 (25.03.2022): 44–56. http://dx.doi.org/10.58845/jstt.utt.2022.en.2.44-56.
Der volle Inhalt der QuelleTran, Anh-Tuan, Thanh-Hai Le und Huu May Nguyen. „Forecast of surface chloride concentration of concrete utilizing ensemble decision tree boosted“. Journal of Science and Transport Technology 2, Nr. 1 (25.03.2022): 44–56. http://dx.doi.org/10.58845/jstt.utt.2022.en.2.1.44-56.
Der volle Inhalt der QuelleZhang, Yupeng, Lin Cheng, Aonan Pan, Chengyang Hu und Kaiming Wu. „Phase Transformation Temperature Prediction in Steels via Machine Learning“. Materials 17, Nr. 5 (29.02.2024): 1117. http://dx.doi.org/10.3390/ma17051117.
Der volle Inhalt der QuelleZhang, Shuai, Emmanuel John M. Carranza, Changliang Fu, Wenzhi Zhang und Xiang Qin. „Interpretable Machine Learning for Geochemical Anomaly Delineation in the Yuanbo Nang District, Gansu Province, China“. Minerals 14, Nr. 5 (10.05.2024): 500. http://dx.doi.org/10.3390/min14050500.
Der volle Inhalt der QuelleKim, Gil-jae, und Byoung-joo Kim. „Analysis of Factors Influencing Satisfaction on Kindergarten Information Disclosure Using Machine Learning“. Korean Society for the Economics and Finance of Education 32, Nr. 3 (30.09.2023): 187–214. http://dx.doi.org/10.46967/jefe.2023.32.3.187.
Der volle Inhalt der QuelleReyes-Urrutia, Andres, Juan Pablo Capossio, Cesar Venier, Erick Torres, Rosa Rodriguez und Germán Mazza. „Artificial Neural Network Prediction of Minimum Fluidization Velocity for Mixtures of Biomass and Inert Solid Particles“. Fluids 8, Nr. 4 (11.04.2023): 128. http://dx.doi.org/10.3390/fluids8040128.
Der volle Inhalt der QuelleLee, Do-Hyun, Sang-Hun Lee, Saem-Ee Woo, Min-Woong Jung, Do-yun Kim und Tae-Young Heo. „Prediction of Complex Odor from Pig Barn Using Machine Learning and Identifying the Influence of Variables Using Explainable Artificial Intelligence“. Applied Sciences 12, Nr. 24 (16.12.2022): 12943. http://dx.doi.org/10.3390/app122412943.
Der volle Inhalt der QuelleQiu, Haijun, Yao Xu, Bingzhe Tang, Lingling Su, Yijun Li, Dongdong Yang und Mohib Ullah. „Interpretable Landslide Susceptibility Evaluation Based on Model Optimization“. Land 13, Nr. 5 (08.05.2024): 639. http://dx.doi.org/10.3390/land13050639.
Der volle Inhalt der QuelleZeng, Yelong, Li Jia, Min Jiang, Chaolei Zheng, Massimo Menenti, Ali Bennour und Yunzhe Lv. „Hydrological Factor and Land Use/Land Cover Change Explain the Vegetation Browning in the Dosso Reserve, Niger“. Remote Sensing 16, Nr. 10 (13.05.2024): 1728. http://dx.doi.org/10.3390/rs16101728.
Der volle Inhalt der QuelleYu, Chenyan, Yao Li, Minyue Yin, Jingwen Gao, Liting Xi, Jiaxi Lin, Lu Liu et al. „Automated Machine Learning in Predicting 30-Day Mortality in Patients with Non-Cholestatic Cirrhosis“. Journal of Personalized Medicine 12, Nr. 11 (19.11.2022): 1930. http://dx.doi.org/10.3390/jpm12111930.
Der volle Inhalt der QuellePassera, Roberto, Sofia Zompi, Jessica Gill und Alessandro Busca. „Explainable Machine Learning (XAI) for Survival in Bone Marrow Transplantation Trials: A Technical Report“. BioMedInformatics 3, Nr. 3 (01.09.2023): 752–68. http://dx.doi.org/10.3390/biomedinformatics3030048.
Der volle Inhalt der QuelleLiu, Chengcheng, Xuandong Wang, Weidong Cai, Yazhou He und Hang Su. „Machine Learning Aided Prediction of Glass-Forming Ability of Metallic Glass“. Processes 11, Nr. 9 (21.09.2023): 2806. http://dx.doi.org/10.3390/pr11092806.
Der volle Inhalt der QuelleGaevskii, A., und D. Diomin. „INFLUENCE OF SOLAR PANELS TILT ANGLE AND GROUND COVER RATIO ON PV PLANT PERFORMANCE“. Alternative Energy and Ecology (ISJAEE), Nr. 25-30 (07.12.2018): 12–24. http://dx.doi.org/10.15518/isjaee.2018.25-30.012-024.
Der volle Inhalt der QuelleFohlmeister, Jürgen F. „Voltage gating by molecular subunits of Na+ and K+ ion channels: higher-dimensional cubic kinetics, rate constants, and temperature“. Journal of Neurophysiology 113, Nr. 10 (Juni 2015): 3759–77. http://dx.doi.org/10.1152/jn.00551.2014.
Der volle Inhalt der QuelleSridhar, Srinivasan, Bradley Whitaker, Amy Mouat-Hunter und Bernadette McCrory. „Predicting Length of Stay using machine learning for total joint replacements performed at a rural community hospital“. PLOS ONE 17, Nr. 11 (10.11.2022): e0277479. http://dx.doi.org/10.1371/journal.pone.0277479.
Der volle Inhalt der QuelleKim, Hyun Woo, Dakota McCarty und Minju Jeong. „Examining Commercial Crime Call Determinants in Alley Commercial Districts before and after COVID-19: A Machine Learning-Based SHAP Approach“. Applied Sciences 13, Nr. 21 (26.10.2023): 11714. http://dx.doi.org/10.3390/app132111714.
Der volle Inhalt der QuelleNagy, Marcell. „Lemorzsolódás előrejelzése személyre szabott értelmezhető gépi tanulási módszerek segítségével“. Scientia et Securitas 3, Nr. 3 (06.04.2023): 270–81. http://dx.doi.org/10.1556/112.2022.00107.
Der volle Inhalt der QuelleWang, Xiaoxiao, Lan Wang, Mingsheng Shang, Lirong Song und Kun Shan. „Revealing Physiochemical Factors and Zooplankton Influencing Microcystis Bloom Toxicity in a Large-Shallow Lake Using Bayesian Machine Learning“. Toxins 14, Nr. 8 (02.08.2022): 530. http://dx.doi.org/10.3390/toxins14080530.
Der volle Inhalt der QuelleHuang, Di, Zhennan Li, Kuo Wang, Haixin Zhou, Xiaojie Zhao, Xinyu Peng, Rui Zhang, Jipeng Wu, Jiaojiao Liang und Ling Zhao. „Probing the Effect of Photovoltaic Material on Voc in Ternary Polymer Solar Cells with Non-Fullerene Acceptors by Machine Learning“. Polymers 15, Nr. 13 (05.07.2023): 2954. http://dx.doi.org/10.3390/polym15132954.
Der volle Inhalt der QuelleGe, Yuankai, Longlong Zhao, Jinsong Chen, Xiaoli Li, Hongzhong Li, Zhengxin Wang und Yanni Ren. „Study on Soil Erosion Driving Forces by Using (R)USLE Framework and Machine Learning: A Case Study in Southwest China“. Land 12, Nr. 3 (08.03.2023): 639. http://dx.doi.org/10.3390/land12030639.
Der volle Inhalt der QuelleFedyk, Tamara. „Memoir structures of the narrative in the play Tetyana Ivashenko «The Mystery of Being»“. Vìsnik Marìupolʹsʹkogo deržavnogo unìversitetu. Serìâ: Fìlologìâ 15, Nr. 26-27 (2022): 194–201. http://dx.doi.org/10.34079/2226-3055-2022-15-26-27-194-201.
Der volle Inhalt der QuelleXia, Yu, Ta Xu, Ming-Xia Wei, Zhen-Ke Wei und Lian-Jie Tang. „Predicting Chain’s Manufacturing SME Credit Risk in Supply Chain Finance Based on Machine Learning Methods“. Sustainability 15, Nr. 2 (06.01.2023): 1087. http://dx.doi.org/10.3390/su15021087.
Der volle Inhalt der QuelleKim, Ki Hong, Jeong Ho Park, Young Sun Ro, Ki Jeong Hong, Kyoung Jun Song und Sang Do Shin. „Emergency department routine data and the diagnosis of acute ischemic heart disease in patients with atypical chest pain“. PLOS ONE 15, Nr. 11 (05.11.2020): e0241920. http://dx.doi.org/10.1371/journal.pone.0241920.
Der volle Inhalt der QuelleShi, Guifang, und Limei Luo. „Prediction and Impact Analysis of Passenger Flow in Urban Rail Transit in the Postpandemic Era“. Journal of Advanced Transportation 2023 (02.08.2023): 1–12. http://dx.doi.org/10.1155/2023/3448864.
Der volle Inhalt der QuelleChoi, Jiyoun. „Exploring influential factors on elementary and middle school students’ reading practice using random forests“. Korean Association For Learner-Centered Curriculum And Instruction 24, Nr. 8 (30.04.2024): 239–50. http://dx.doi.org/10.22251/jlcci.2024.24.8.239.
Der volle Inhalt der QuelleGreenwell, Brandon,M. „pdp: An R Package for Constructing Partial Dependence Plots“. R Journal 9, Nr. 1 (2017): 421. http://dx.doi.org/10.32614/rj-2017-016.
Der volle Inhalt der QuelleJohnson, Phillip, Anna Trybala und Victor Starov. „Kinetics of Spreading over Porous Substrates“. Colloids and Interfaces 3, Nr. 1 (15.03.2019): 38. http://dx.doi.org/10.3390/colloids3010038.
Der volle Inhalt der QuelleSpinolo, Giorgio, Umberto Anselmi-Tamburini und Paolo Ghigna. „An Exact and Simple Approach to log-log Plots for Defect and Ionic Equilibria“. Zeitschrift für Naturforschung A 52, Nr. 8-9 (01.09.1997): 629–36. http://dx.doi.org/10.1515/zna-1997-8-914.
Der volle Inhalt der QuelleZhang, Weichun, Yunyi Zhang, Xin Zhang, Wei Wu und Hongbin Liu. „The Spatiotemporal Variability of Soil Available Phosphorus and Potassium in Karst Region: The Crucial Role of Socio-Geographical Factors“. Land 13, Nr. 6 (18.06.2024): 882. http://dx.doi.org/10.3390/land13060882.
Der volle Inhalt der QuelleShyr, David C., Bing Melody Zhang, Robertson Parkman und Simon E. Brewer. „Machine Learning Methods to Better Predict Post-Hematopoietic Stem Cell Transplant (HSCT) Leukemic Relapse in Pediatric Patients with Acute Lymphoblastic Leukemia: Random Forest (RF) Classification Featuring Serial Post-Transplant Lineage-Specific Chimerism“. Blood 136, Supplement 1 (05.11.2020): 6–7. http://dx.doi.org/10.1182/blood-2020-139104.
Der volle Inhalt der QuelleZhao, Xiaohua, Haiyi Yang, Ying Yao, Hang Qi, Miao Guo und Yuelong Su. „Factors affecting traffic risks on bridge sections of freeways based on partial dependence plots“. Physica A: Statistical Mechanics and its Applications 598 (Juli 2022): 127343. http://dx.doi.org/10.1016/j.physa.2022.127343.
Der volle Inhalt der QuelleShi, Haoze, Naisen Yang, Xin Yang und Hong Tang. „Clarifying Relationship between PM2.5 Concentrations and Spatiotemporal Predictors Using Multi-Way Partial Dependence Plots“. Remote Sensing 15, Nr. 2 (06.01.2023): 358. http://dx.doi.org/10.3390/rs15020358.
Der volle Inhalt der QuelleBaidada, Chafik, Hamid Hrimech, Mustapha Aatila, Mohamed Lachgar und Younes Ommane. „Machine learning for real-time prediction of complications induced by flexible uretero-renoscopy with laser lithotripsy“. International Journal of Electrical and Computer Engineering (IJECE) 14, Nr. 1 (01.02.2024): 971. http://dx.doi.org/10.11591/ijece.v14i1.pp971-982.
Der volle Inhalt der QuelleSzepannaek, Gero, und Karsten Lübke. „How much do we see? On the explainability of partial dependence plots for credit risk scoring“. Argumenta Oeconomica 2023, Nr. 2 (2023): 137–50. http://dx.doi.org/10.15611/aoe.2023.1.07.
Der volle Inhalt der QuelleJohnson, Paul M., William Barbour, Janey V. Camp und Hiba Baroud. „Using machine learning to examine freight network spatial vulnerabilities to disasters: A new take on partial dependence plots“. Transportation Research Interdisciplinary Perspectives 14 (Juni 2022): 100617. http://dx.doi.org/10.1016/j.trip.2022.100617.
Der volle Inhalt der QuelleBegum, Zareena, P. B. Sandhya Sri, D. B. Karuna Kumar, K. Rayapa Reddy und C. Rambabu. „Partial molar volumes partial molar adiabatic compressibilities and molar Gibbs energies of anisaldehyde with some alkoxyethanols — Insights through plots showing compositional, volumetric and temperature dependence“. Journal of Molecular Liquids 184 (August 2013): 33–42. http://dx.doi.org/10.1016/j.molliq.2013.04.007.
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