Artigos de revistas sobre o tema "Partial Dependence Plot"
Crie uma referência precisa em APA, MLA, Chicago, Harvard, e outros estilos
Veja os 50 melhores artigos de revistas para estudos sobre o assunto "Partial Dependence Plot".
Ao lado de cada fonte na lista de referências, há um botão "Adicionar à bibliografia". Clique e geraremos automaticamente a citação bibliográfica do trabalho escolhido no estilo de citação de que você precisa: APA, MLA, Harvard, Chicago, Vancouver, etc.
Você também pode baixar o texto completo da publicação científica em formato .pdf e ler o resumo do trabalho online se estiver presente nos metadados.
Veja os artigos de revistas das mais diversas áreas científicas e compile uma bibliografia correta.
Yan, Miaomiao, e Yindong Shen. "Traffic Accident Severity Prediction Based on Random Forest". Sustainability 14, n.º 3 (2 de fevereiro de 2022): 1729. http://dx.doi.org/10.3390/su14031729.
Texto completo da fonteDewan, Isha, e Subhash Kochar. "SOME NEW APPLICATIONS OF P–P PLOTS". Probability in the Engineering and Informational Sciences 27, n.º 3 (28 de março de 2013): 353–66. http://dx.doi.org/10.1017/s0269964813000077.
Texto completo da fonteLee, Changro. "Training and Interpreting Machine Learning Models: Application in Property Tax Assessment". Real Estate Management and Valuation 30, n.º 1 (1 de março de 2022): 13–22. http://dx.doi.org/10.2478/remav-2022-0002.
Texto completo da fonteFu, Xiao. "The D e (T, t) plot: A straightforward self-diagnose tool for post-IR IRSL dating procedures". Geochronometria 41, n.º 4 (1 de dezembro de 2014): 315–26. http://dx.doi.org/10.2478/s13386-013-0167-9.
Texto completo da fonteTran, Van Quan. "Predicting and Investigating the Permeability Coefficient of Soil with Aided Single Machine Learning Algorithm". Complexity 2022 (25 de setembro de 2022): 1–18. http://dx.doi.org/10.1155/2022/8089428.
Texto completo da fonteWu, Zihao, Yiyun Chen, Yuanli Zhu, Xiangyang Feng, Jianxiong Ou, Guie Li, Zhaomin Tong e Qingwu Yan. "Mapping Soil Organic Carbon in Floodplain Farmland: Implications of Effective Range of Environmental Variables". Land 12, n.º 6 (8 de junho de 2023): 1198. http://dx.doi.org/10.3390/land12061198.
Texto completo da fontePatterson, L. D., e 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, n.º 2 (fevereiro de 2020): 105–16. http://dx.doi.org/10.1139/cjz-2019-0166.
Texto completo da fonteKhoerunnisa, 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.
Texto completo da fonteChang, Shih-Chieh, Chan-Lin Chu, Chih-Kuang Chen, Hsiang-Ning Chang, Alice M. K. Wong, Yueh-Peng Chen e Yu-Cheng Pei. "The Comparison and Interpretation of Machine-Learning Models in Post-Stroke Functional Outcome Prediction". Diagnostics 11, n.º 10 (28 de setembro de 2021): 1784. http://dx.doi.org/10.3390/diagnostics11101784.
Texto completo da fonteShiroyama, Risa, Manna Wang e 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.
Texto completo da fonteLin, Ming-Yen, Yuan-Ming Chang, Chi-Chun Li e Wen-Cheng Chao. "Explainable Machine Learning to Predict Successful Weaning of Mechanical Ventilation in Critically Ill Patients Requiring Hemodialysis". Healthcare 11, n.º 6 (21 de março de 2023): 910. http://dx.doi.org/10.3390/healthcare11060910.
Texto completo da fonteNúñez, Jorge, Catalina B. Cortés e 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, n.º 19 (26 de setembro de 2023): 3369. http://dx.doi.org/10.3390/w15193369.
Texto completo da fonteTran, Anh-Tuan, Thanh-Hai Le e Huu May Nguyen. "Forecast of surface chloride concentration of concrete utilizing ensemble decision tree boosted". Journal of Science and Transport Technology 2, n.º 1 (25 de março de 2022): 44–56. http://dx.doi.org/10.58845/jstt.utt.2022.en57.
Texto completo da fonteJung, Jinwoo, Jihwan Kim e Changha Jin. "DOES MACHINE LEARNING PREDICTION DAMPEN THE INFORMATION ASYMMETRY FOR NON-LOCAL INVESTORS?" International Journal of Strategic Property Management 26, n.º 5 (14 de novembro de 2022): 345–61. http://dx.doi.org/10.3846/ijspm.2022.17590.
Texto completo da fonteTran, Anh-Tuan, Thanh-Hai Le e Huu May Nguyen. "Forecast of surface chloride concentration of concrete utilizing ensemble decision tree boosted". Journal of Science and Transport Technology 2, n.º 1 (25 de março de 2022): 44–56. http://dx.doi.org/10.58845/jstt.utt.2022.en.2.44-56.
Texto completo da fonteTran, Anh-Tuan, Thanh-Hai Le e Huu May Nguyen. "Forecast of surface chloride concentration of concrete utilizing ensemble decision tree boosted". Journal of Science and Transport Technology 2, n.º 1 (25 de março de 2022): 44–56. http://dx.doi.org/10.58845/jstt.utt.2022.en.2.1.44-56.
Texto completo da fonteZhang, Yupeng, Lin Cheng, Aonan Pan, Chengyang Hu e Kaiming Wu. "Phase Transformation Temperature Prediction in Steels via Machine Learning". Materials 17, n.º 5 (29 de fevereiro de 2024): 1117. http://dx.doi.org/10.3390/ma17051117.
Texto completo da fonteZhang, Shuai, Emmanuel John M. Carranza, Changliang Fu, Wenzhi Zhang e Xiang Qin. "Interpretable Machine Learning for Geochemical Anomaly Delineation in the Yuanbo Nang District, Gansu Province, China". Minerals 14, n.º 5 (10 de maio de 2024): 500. http://dx.doi.org/10.3390/min14050500.
Texto completo da fonteKim, Gil-jae, e 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, n.º 3 (30 de setembro de 2023): 187–214. http://dx.doi.org/10.46967/jefe.2023.32.3.187.
Texto completo da fonteReyes-Urrutia, Andres, Juan Pablo Capossio, Cesar Venier, Erick Torres, Rosa Rodriguez e Germán Mazza. "Artificial Neural Network Prediction of Minimum Fluidization Velocity for Mixtures of Biomass and Inert Solid Particles". Fluids 8, n.º 4 (11 de abril de 2023): 128. http://dx.doi.org/10.3390/fluids8040128.
Texto completo da fonteLee, Do-Hyun, Sang-Hun Lee, Saem-Ee Woo, Min-Woong Jung, Do-yun Kim e 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, n.º 24 (16 de dezembro de 2022): 12943. http://dx.doi.org/10.3390/app122412943.
Texto completo da fonteQiu, Haijun, Yao Xu, Bingzhe Tang, Lingling Su, Yijun Li, Dongdong Yang e Mohib Ullah. "Interpretable Landslide Susceptibility Evaluation Based on Model Optimization". Land 13, n.º 5 (8 de maio de 2024): 639. http://dx.doi.org/10.3390/land13050639.
Texto completo da fonteZeng, Yelong, Li Jia, Min Jiang, Chaolei Zheng, Massimo Menenti, Ali Bennour e Yunzhe Lv. "Hydrological Factor and Land Use/Land Cover Change Explain the Vegetation Browning in the Dosso Reserve, Niger". Remote Sensing 16, n.º 10 (13 de maio de 2024): 1728. http://dx.doi.org/10.3390/rs16101728.
Texto completo da fonteYu, 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, n.º 11 (19 de novembro de 2022): 1930. http://dx.doi.org/10.3390/jpm12111930.
Texto completo da fontePassera, Roberto, Sofia Zompi, Jessica Gill e Alessandro Busca. "Explainable Machine Learning (XAI) for Survival in Bone Marrow Transplantation Trials: A Technical Report". BioMedInformatics 3, n.º 3 (1 de setembro de 2023): 752–68. http://dx.doi.org/10.3390/biomedinformatics3030048.
Texto completo da fonteLiu, Chengcheng, Xuandong Wang, Weidong Cai, Yazhou He e Hang Su. "Machine Learning Aided Prediction of Glass-Forming Ability of Metallic Glass". Processes 11, n.º 9 (21 de setembro de 2023): 2806. http://dx.doi.org/10.3390/pr11092806.
Texto completo da fonteGaevskii, A., e D. Diomin. "INFLUENCE OF SOLAR PANELS TILT ANGLE AND GROUND COVER RATIO ON PV PLANT PERFORMANCE". Alternative Energy and Ecology (ISJAEE), n.º 25-30 (7 de dezembro de 2018): 12–24. http://dx.doi.org/10.15518/isjaee.2018.25-30.012-024.
Texto completo da fonteFohlmeister, 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, n.º 10 (junho de 2015): 3759–77. http://dx.doi.org/10.1152/jn.00551.2014.
Texto completo da fonteSridhar, Srinivasan, Bradley Whitaker, Amy Mouat-Hunter e Bernadette McCrory. "Predicting Length of Stay using machine learning for total joint replacements performed at a rural community hospital". PLOS ONE 17, n.º 11 (10 de novembro de 2022): e0277479. http://dx.doi.org/10.1371/journal.pone.0277479.
Texto completo da fonteKim, Hyun Woo, Dakota McCarty e 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, n.º 21 (26 de outubro de 2023): 11714. http://dx.doi.org/10.3390/app132111714.
Texto completo da fonteNagy, Marcell. "Lemorzsolódás előrejelzése személyre szabott értelmezhető gépi tanulási módszerek segítségével". Scientia et Securitas 3, n.º 3 (6 de abril de 2023): 270–81. http://dx.doi.org/10.1556/112.2022.00107.
Texto completo da fonteWang, Xiaoxiao, Lan Wang, Mingsheng Shang, Lirong Song e Kun Shan. "Revealing Physiochemical Factors and Zooplankton Influencing Microcystis Bloom Toxicity in a Large-Shallow Lake Using Bayesian Machine Learning". Toxins 14, n.º 8 (2 de agosto de 2022): 530. http://dx.doi.org/10.3390/toxins14080530.
Texto completo da fonteHuang, Di, Zhennan Li, Kuo Wang, Haixin Zhou, Xiaojie Zhao, Xinyu Peng, Rui Zhang, Jipeng Wu, Jiaojiao Liang e Ling Zhao. "Probing the Effect of Photovoltaic Material on Voc in Ternary Polymer Solar Cells with Non-Fullerene Acceptors by Machine Learning". Polymers 15, n.º 13 (5 de julho de 2023): 2954. http://dx.doi.org/10.3390/polym15132954.
Texto completo da fonteGe, Yuankai, Longlong Zhao, Jinsong Chen, Xiaoli Li, Hongzhong Li, Zhengxin Wang e Yanni Ren. "Study on Soil Erosion Driving Forces by Using (R)USLE Framework and Machine Learning: A Case Study in Southwest China". Land 12, n.º 3 (8 de março de 2023): 639. http://dx.doi.org/10.3390/land12030639.
Texto completo da fonteFedyk, Tamara. "Memoir structures of the narrative in the play Tetyana Ivashenko «The Mystery of Being»". Vìsnik Marìupolʹsʹkogo deržavnogo unìversitetu. Serìâ: Fìlologìâ 15, n.º 26-27 (2022): 194–201. http://dx.doi.org/10.34079/2226-3055-2022-15-26-27-194-201.
Texto completo da fonteXia, Yu, Ta Xu, Ming-Xia Wei, Zhen-Ke Wei e Lian-Jie Tang. "Predicting Chain’s Manufacturing SME Credit Risk in Supply Chain Finance Based on Machine Learning Methods". Sustainability 15, n.º 2 (6 de janeiro de 2023): 1087. http://dx.doi.org/10.3390/su15021087.
Texto completo da fonteKim, Ki Hong, Jeong Ho Park, Young Sun Ro, Ki Jeong Hong, Kyoung Jun Song e Sang Do Shin. "Emergency department routine data and the diagnosis of acute ischemic heart disease in patients with atypical chest pain". PLOS ONE 15, n.º 11 (5 de novembro de 2020): e0241920. http://dx.doi.org/10.1371/journal.pone.0241920.
Texto completo da fonteShi, Guifang, e Limei Luo. "Prediction and Impact Analysis of Passenger Flow in Urban Rail Transit in the Postpandemic Era". Journal of Advanced Transportation 2023 (2 de agosto de 2023): 1–12. http://dx.doi.org/10.1155/2023/3448864.
Texto completo da fonteChoi, Jiyoun. "Exploring influential factors on elementary and middle school students’ reading practice using random forests". Korean Association For Learner-Centered Curriculum And Instruction 24, n.º 8 (30 de abril de 2024): 239–50. http://dx.doi.org/10.22251/jlcci.2024.24.8.239.
Texto completo da fonteGreenwell, Brandon,M. "pdp: An R Package for Constructing Partial Dependence Plots". R Journal 9, n.º 1 (2017): 421. http://dx.doi.org/10.32614/rj-2017-016.
Texto completo da fonteJohnson, Phillip, Anna Trybala e Victor Starov. "Kinetics of Spreading over Porous Substrates". Colloids and Interfaces 3, n.º 1 (15 de março de 2019): 38. http://dx.doi.org/10.3390/colloids3010038.
Texto completo da fonteSpinolo, Giorgio, Umberto Anselmi-Tamburini e Paolo Ghigna. "An Exact and Simple Approach to log-log Plots for Defect and Ionic Equilibria". Zeitschrift für Naturforschung A 52, n.º 8-9 (1 de setembro de 1997): 629–36. http://dx.doi.org/10.1515/zna-1997-8-914.
Texto completo da fonteZhang, Weichun, Yunyi Zhang, Xin Zhang, Wei Wu e Hongbin Liu. "The Spatiotemporal Variability of Soil Available Phosphorus and Potassium in Karst Region: The Crucial Role of Socio-Geographical Factors". Land 13, n.º 6 (18 de junho de 2024): 882. http://dx.doi.org/10.3390/land13060882.
Texto completo da fonteShyr, David C., Bing Melody Zhang, Robertson Parkman e 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 (5 de novembro de 2020): 6–7. http://dx.doi.org/10.1182/blood-2020-139104.
Texto completo da fonteZhao, Xiaohua, Haiyi Yang, Ying Yao, Hang Qi, Miao Guo e Yuelong Su. "Factors affecting traffic risks on bridge sections of freeways based on partial dependence plots". Physica A: Statistical Mechanics and its Applications 598 (julho de 2022): 127343. http://dx.doi.org/10.1016/j.physa.2022.127343.
Texto completo da fonteShi, Haoze, Naisen Yang, Xin Yang e Hong Tang. "Clarifying Relationship between PM2.5 Concentrations and Spatiotemporal Predictors Using Multi-Way Partial Dependence Plots". Remote Sensing 15, n.º 2 (6 de janeiro de 2023): 358. http://dx.doi.org/10.3390/rs15020358.
Texto completo da fonteBaidada, Chafik, Hamid Hrimech, Mustapha Aatila, Mohamed Lachgar e 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, n.º 1 (1 de fevereiro de 2024): 971. http://dx.doi.org/10.11591/ijece.v14i1.pp971-982.
Texto completo da fonteSzepannaek, Gero, e Karsten Lübke. "How much do we see? On the explainability of partial dependence plots for credit risk scoring". Argumenta Oeconomica 2023, n.º 2 (2023): 137–50. http://dx.doi.org/10.15611/aoe.2023.1.07.
Texto completo da fonteJohnson, Paul M., William Barbour, Janey V. Camp e 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 (junho de 2022): 100617. http://dx.doi.org/10.1016/j.trip.2022.100617.
Texto completo da fonteBegum, Zareena, P. B. Sandhya Sri, D. B. Karuna Kumar, K. Rayapa Reddy e 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 (agosto de 2013): 33–42. http://dx.doi.org/10.1016/j.molliq.2013.04.007.
Texto completo da fonte