Journal articles on the topic 'Random Forest predictive model'
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Mohnen, Sigrid M., Adriënne H. Rotteveel, Gerda Doornbos, and Johan J. Polder. "Healthcare Expenditure Prediction with Neighbourhood Variables – A Random Forest Model." Statistics, Politics and Policy 11, no. 2 (December 16, 2020): 111–38. http://dx.doi.org/10.1515/spp-2019-0010.
Full textWang, Fangyi, Yongchao Wang, Xiaokang Ji, and Zhiping Wang. "Effective Macrosomia Prediction Using Random Forest Algorithm." International Journal of Environmental Research and Public Health 19, no. 6 (March 10, 2022): 3245. http://dx.doi.org/10.3390/ijerph19063245.
Full textKor, Hakan. "Global solar radiation prediction model with random forest algorithm." Thermal Science 25, Spec. issue 1 (2021): 31–39. http://dx.doi.org/10.2298/tsci200608004k.
Full textRigatti, Steven J. "Random Forest." Journal of Insurance Medicine 47, no. 1 (January 1, 2017): 31–39. http://dx.doi.org/10.17849/insm-47-01-31-39.1.
Full textWei, Li-Li, Yue-Shuai Pan, Yan Zhang, Kai Chen, Hao-Yu Wang, and Jing-Yuan Wang. "Application of machine learning algorithm for predicting gestational diabetes mellitus in early pregnancy†." Frontiers of Nursing 8, no. 3 (September 1, 2021): 209–21. http://dx.doi.org/10.2478/fon-2021-0022.
Full textDiaz, Pablo, Juan C. Salas, Aldo Cipriano, and Felipe Núñez. "Random forest model predictive control for paste thickening." Minerals Engineering 163 (March 2021): 106760. http://dx.doi.org/10.1016/j.mineng.2020.106760.
Full textMao, Yiwen, and Asgeir Sorteberg. "Improving Radar-Based Precipitation Nowcasts with Machine Learning Using an Approach Based on Random Forest." Weather and Forecasting 35, no. 6 (December 2020): 2461–78. http://dx.doi.org/10.1175/waf-d-20-0080.1.
Full textBashir Suleiman, Aminu, Stephen Luka, and Muhammad Ibrahim. "CARDIOVASCULAR DISEASE PREDICTION USING RANDOM FOREST MACHINE LEARNING ALGORITHM." FUDMA JOURNAL OF SCIENCES 7, no. 6 (December 31, 2023): 282–89. http://dx.doi.org/10.33003/fjs-2023-0706-2128.
Full textJeong, Hoyeon, Youngjune Kim, and So Yeong Lim. "A Predictive Model for Farmland Purchase/Rent Using Random Forests." Korean Agricultural Economics Association 63, no. 3 (September 30, 2022): 153–68. http://dx.doi.org/10.24997/kjae.2022.63.3.153.
Full textEmir, Senol, Hasan Dincer, Umit Hacioglu, and Serhat Yuksel. "Random Regression Forest Model using Technical Analysis Variables." International Journal of Finance & Banking Studies (2147-4486) 5, no. 3 (July 21, 2016): 85–102. http://dx.doi.org/10.20525/ijfbs.v5i3.461.
Full textNie, Ying, and Yundong Xu. "Prediction On Tiktok Like Behavior Based on Random Forest Model." Highlights in Science, Engineering and Technology 101 (May 20, 2024): 292–98. http://dx.doi.org/10.54097/d6metn07.
Full textRen, Keying. "House Price Prediction Based on Machine Learning Algorithms - Taking Ames as an Example." Advances in Economics, Management and Political Sciences 85, no. 1 (May 28, 2024): 181–89. http://dx.doi.org/10.54254/2754-1169/85/20240870.
Full textMathew, Dr Tina Elizabeth. "An Improvised Random Forest Model for Breast Cancer Classification." NeuroQuantology 20, no. 5 (May 18, 2022): 713–22. http://dx.doi.org/10.14704/nq.2022.20.5.nq22227.
Full textWang, Zijie, Yufang Bi, Gang Lu, Xu Zhang, Xiangyang Xu, Yilin Ning, Xuhua Du, and Anke Wang. "Monitoring Forest Diversity under Moso Bamboo Invasion: A Random Forest Approach." Forests 15, no. 2 (February 7, 2024): 318. http://dx.doi.org/10.3390/f15020318.
Full textZhou, Shu-Ping, Su-Ding Fei, Hui-Hui Han, Jing-Jing Li, Shuang Yang, and Chun-Yang Zhao. "A Prediction Model for Cognitive Impairment Risk in Colorectal Cancer after Chemotherapy Treatment." BioMed Research International 2021 (February 20, 2021): 1–13. http://dx.doi.org/10.1155/2021/6666453.
Full textROHAJAWATI, Siti, Hutanti SETYODEWI, Ferryansyah Muji Agustian TRESNANTO, Debora MARIANTHI, and Maruli Tua Baja SIHOTANG. "KNOWLEDGE MANAGEMENT APPROACH IN COMPARATIVE STUDY OF AIR POLLUTION PREDICTION MODEL." Applied Computer Science 20, no. 1 (March 30, 2024): 173–88. http://dx.doi.org/10.35784/acs-2024-11.
Full textYu, Chenghao. "Walmart Sales Forecasting using Different Models." Highlights in Science, Engineering and Technology 92 (April 10, 2024): 302–7. http://dx.doi.org/10.54097/kqf76062.
Full textYan, Miaomiao, and Yindong Shen. "Traffic Accident Severity Prediction Based on Random Forest." Sustainability 14, no. 3 (February 2, 2022): 1729. http://dx.doi.org/10.3390/su14031729.
Full textLiu, Qian, Wanyin Qi, Yanping Wu, Yingjun Zhou, and Zhiwei Huang. "Construction of Pulmonary Nodule CT Radiomics Random Forest Model Based on Artificial Intelligence Software for STAS Evaluation of Stage IA Lung Adenocarcinoma." Computational and Mathematical Methods in Medicine 2022 (August 28, 2022): 1–6. http://dx.doi.org/10.1155/2022/2173412.
Full textWang, Hao, He Zhang, Jia Zhao, Xinyi Liu, Xinyue Feng, and Yinuo Sun. "Product order-demand prediction model based on random forest." Highlights in Business, Economics and Management 18 (October 15, 2023): 383–90. http://dx.doi.org/10.54097/hbem.v18i.12735.
Full textYadav, Pradeep, Chandra Prakash Bhargava, Deepak Gupta, Jyoti Kumari, Archana Acharya, and Madhukar Dubey. "Breast Cancer Disease Prediction Using Random Forest Regression and Gradient Boosting Regression." International Journal of Experimental Research and Review 38 (April 30, 2024): 132–46. http://dx.doi.org/10.52756/ijerr.2024.v38.012.
Full textNie, Shunqi, Honghua Chen, Xinxin Sun, and Yunce An. "Spatial Distribution Prediction of Soil Heavy Metals Based on Random Forest Model." Sustainability 16, no. 11 (May 22, 2024): 4358. http://dx.doi.org/10.3390/su16114358.
Full textHujare, Pravin, Praveen Rathod, Dinesh Kamble, Amit Jomde, and Shalini Wankhede. "Predictive analytics of disc brake deformation using machine learning." Journal of Information and Optimization Sciences 45, no. 4 (2024): 1153–63. http://dx.doi.org/10.47974/jios-1699.
Full textDivya Chilukuri, Akhila Tejaswini. K, Prathyusha. K, and Anjali. N. "A review on predictive model for Autisim spectrum disorder." World Journal of Advanced Engineering Technology and Sciences 12, no. 1 (May 30, 2024): 218–21. http://dx.doi.org/10.30574/wjaets.2024.12.1.0204.
Full textBozorgmehr, Arezoo, Anika Thielmann, and Birgitta Weltermann. "Chronic stress in practice assistants: An analytic approach comparing four machine learning classifiers with a standard logistic regression model." PLOS ONE 16, no. 5 (May 4, 2021): e0250842. http://dx.doi.org/10.1371/journal.pone.0250842.
Full textLee, Seung-hyeong, and Eun-Ju Baek. "Development of a predictive model for university students’ core competency index using machine learning: Focusing on D University." Korean Association For Learner-Centered Curriculum And Instruction 22, no. 11 (June 15, 2022): 831–49. http://dx.doi.org/10.22251/jlcci.2022.22.11.831.
Full textGroll, Andreas, Cristophe Ley, Gunther Schauberger, and Hans Van Eetvelde. "A hybrid random forest to predict soccer matches in international tournaments." Journal of Quantitative Analysis in Sports 15, no. 4 (October 25, 2019): 271–87. http://dx.doi.org/10.1515/jqas-2018-0060.
Full textMao, Mohan. "A Comparative Study of Random Forest Regression for Predicting House Prices Using." Highlights in Science, Engineering and Technology 85 (March 13, 2024): 969–74. http://dx.doi.org/10.54097/bdfe8032.
Full textZhou, Jing, Yuzhen Li, and Xuan Guo. "Predicting psoriasis using routine laboratory tests with random forest." PLOS ONE 16, no. 10 (October 19, 2021): e0258768. http://dx.doi.org/10.1371/journal.pone.0258768.
Full textShao, Yakui, Zhongke Feng, Meng Cao, Wenbiao Wang, Linhao Sun, Xuanhan Yang, Tiantian Ma, et al. "An Ensemble Model for Forest Fire Occurrence Mapping in China." Forests 14, no. 4 (March 29, 2023): 704. http://dx.doi.org/10.3390/f14040704.
Full textChao Gao. "Balancing Interpretability and Performance: Optimizing Random Forest Algorithm Based on Point-to-Point Federated Learning." Journal of Electrical Systems 20, no. 7s (May 4, 2024): 2389–400. http://dx.doi.org/10.52783/jes.3990.
Full textTruong, Tran Xuan, Viet-Ha Nhu, Doan Thi Nam Phuong, Le Thanh Nghi, Nguyen Nhu Hung, Pham Viet Hoa, and Dieu Tien Bui. "A New Approach Based on TensorFlow Deep Neural Networks with ADAM Optimizer and GIS for Spatial Prediction of Forest Fire Danger in Tropical Areas." Remote Sensing 15, no. 14 (July 8, 2023): 3458. http://dx.doi.org/10.3390/rs15143458.
Full textLee, Soo-Kyoung, Juh Hyun Shin, Jinhyun Ahn, Ji Yeon Lee, and Dong Eun Jang. "Identifying the Risk Factors Associated with Nursing Home Residents’ Pressure Ulcers Using Machine Learning Methods." International Journal of Environmental Research and Public Health 18, no. 6 (March 13, 2021): 2954. http://dx.doi.org/10.3390/ijerph18062954.
Full textMalhi, Ramandeep Kaur M., Akash Anand, Prashant K. Srivastava, G. Sandhya Kiran, George P. Petropoulos, and Christos Chalkias. "An Integrated Spatiotemporal Pattern Analysis Model to Assess and Predict the Degradation of Protected Forest Areas." ISPRS International Journal of Geo-Information 9, no. 9 (September 2, 2020): 530. http://dx.doi.org/10.3390/ijgi9090530.
Full textSaladi, Sarojini Devi, and Radhika Yarlagadda. "An Enhanced Bankruptcy Prediction Model Using Fuzzy Clustering Model and Random Forest Algorithm." Revue d'Intelligence Artificielle 35, no. 1 (February 28, 2021): 77–83. http://dx.doi.org/10.18280/ria.350109.
Full textLe, Ngoc-Bich, Thi-Thu-Hien Pham, Sy-Hoang Nguyen, Nhat-Minh Nguyen, and Tan-Nhu Nguyen. "AI-powered Predictive Model for Stroke and Diabetes Diagnostic." International Journal of Intelligent Systems and Applications 16, no. 1 (February 8, 2024): 24–40. http://dx.doi.org/10.5815/ijisa.2024.01.03.
Full textRuyssinck, Joeri, Joachim van der Herten, Rein Houthooft, Femke Ongenae, Ivo Couckuyt, Bram Gadeyne, Kirsten Colpaert, Johan Decruyenaere, Filip De Turck, and Tom Dhaene. "Random Survival Forests for Predicting the Bed Occupancy in the Intensive Care Unit." Computational and Mathematical Methods in Medicine 2016 (2016): 1–7. http://dx.doi.org/10.1155/2016/7087053.
Full textAlfraihat, Ausilah, Amer F. Samdani, and Sriram Balasubramanian. "Predicting curve progression for adolescent idiopathic scoliosis using random forest model." PLOS ONE 17, no. 8 (August 11, 2022): e0273002. http://dx.doi.org/10.1371/journal.pone.0273002.
Full textLei, Xiaoli. "Resource Sharing Algorithm of Ideological and Political Course Based on Random Forest." Mathematical Problems in Engineering 2022 (May 21, 2022): 1–8. http://dx.doi.org/10.1155/2022/8765166.
Full textQi, Yuxuan. "Research on Stock Price Prediction Based on LSTM Model and Random Forest." Advances in Economics, Management and Political Sciences 86, no. 1 (May 28, 2024): 35–42. http://dx.doi.org/10.54254/2754-1169/86/20240938.
Full textBayramli, Ilkin, Victor Castro, Yuval Barak-Corren, Emily M. Madsen, Matthew K. Nock, Jordan W. Smoller, and Ben Y. Reis. "Temporally informed random forests for suicide risk prediction." Journal of the American Medical Informatics Association 29, no. 1 (November 2, 2021): 62–71. http://dx.doi.org/10.1093/jamia/ocab225.
Full textBayramli, Ilkin, Victor Castro, Yuval Barak-Corren, Emily M. Madsen, Matthew K. Nock, Jordan W. Smoller, and Ben Y. Reis. "Temporally informed random forests for suicide risk prediction." Journal of the American Medical Informatics Association 29, no. 1 (November 2, 2021): 62–71. http://dx.doi.org/10.1093/jamia/ocab225.
Full textWang, Shihao, and Xiangxiang Wu. "The Mechanical Performance Prediction of Steel Materials based on Random Forest." Frontiers in Computing and Intelligent Systems 6, no. 1 (November 27, 2023): 1–3. http://dx.doi.org/10.54097/fcis.v6i1.01.
Full textNikolopoulos, Efthymios I., Elisa Destro, Md Abul Ehsan Bhuiyan, Marco Borga, and Emmanouil N. Anagnostou. "Evaluation of predictive models for post-fire debris flow occurrence in the western United States." Natural Hazards and Earth System Sciences 18, no. 9 (September 4, 2018): 2331–43. http://dx.doi.org/10.5194/nhess-18-2331-2018.
Full textGold, Ochim, and Agaji Iorshase. "Heart failure prediction framework using random forest and J48 with Adaboost algorithms." Science World Journal 18, no. 2 (October 20, 2023): 165–75. http://dx.doi.org/10.4314/swj.v18i2.1.
Full textGuo, Shengnan, and Jianqiu Xu. "CPRQ: Cost Prediction for Range Queries in Moving Object Databases." ISPRS International Journal of Geo-Information 10, no. 7 (July 8, 2021): 468. http://dx.doi.org/10.3390/ijgi10070468.
Full textFernández-Carrillo, Ángel, Antonio Franco-Nieto, María Julia Yagüe-Ballester, and Marta Gómez-Giménez. "Predictive Model for Bark Beetle Outbreaks in European Forests." Forests 15, no. 7 (June 27, 2024): 1114. http://dx.doi.org/10.3390/f15071114.
Full textERSHOV, EVGENY V., OLGA V. YUDINA, LYUDMILA N. VINOGRADOVA, and NIKITA I. SHAKHANOV. "EQUIPMENT CONDITION MODELING BASED ON RANDOM FOREST AND ARIMA MACHINE LEARNING ALGORITHM STACKING." Cherepovets State University Bulletin 4, no. 97 (2020): 32–40. http://dx.doi.org/10.23859/1994-0637-2020-4-97-3.
Full textHuan, Juan, Bo Chen, Xian Gen Xu, Hui Li, Ming Bao Li, and Hao Zhang. "River Dissolved Oxygen Prediction Based on Random Forest and LSTM." Applied Engineering in Agriculture 37, no. 5 (2021): 901–10. http://dx.doi.org/10.13031/aea.14496.
Full textQu, Chaoran, Xiufen Yang, Weisi Peng, Xiujuan Wang, and Weixiang Luo. "THE PREDICTIVE EFFECT OF DIFFERENT MACHINE LEARNING ALGORITHMS FOR PRESSURE INJURIES: A NETWORK META-ANALYSES." Innovation in Aging 7, Supplement_1 (December 1, 2023): 1178. http://dx.doi.org/10.1093/geroni/igad104.3776.
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