Artículos de revistas sobre el tema "ENSEMBLE LEARNING TECHNIQUE"
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ACOSTA-MENDOZA, NIUSVEL, ALICIA MORALES-REYES, HUGO JAIR ESCALANTE y ANDRÉS GAGO-ALONSO. "LEARNING TO ASSEMBLE CLASSIFIERS VIA GENETIC PROGRAMMING". International Journal of Pattern Recognition and Artificial Intelligence 28, n.º 07 (14 de octubre de 2014): 1460005. http://dx.doi.org/10.1142/s0218001414600052.
Texto completoReddy, S. Pavan Kumar y U. Sesadri. "A Bootstrap Aggregating Technique on Link-Based Cluster Ensemble Approach for Categorical Data Clustering". INTERNATIONAL JOURNAL OF COMPUTERS & TECHNOLOGY 10, n.º 8 (30 de agosto de 2013): 1913–21. http://dx.doi.org/10.24297/ijct.v10i8.1468.
Texto completoGoyal, Jyotsana. "IMPROVING CLASSIFICATION PERFORMANCE USING ENSEMBLE LEARNING APPROACH". BSSS Journal of Computer 14, n.º 1 (30 de junio de 2023): 63–75. http://dx.doi.org/10.51767/jc1409.
Texto completoCawood, Pieter y Terence Van Zyl. "Evaluating State-of-the-Art, Forecasting Ensembles and Meta-Learning Strategies for Model Fusion". Forecasting 4, n.º 3 (18 de agosto de 2022): 732–51. http://dx.doi.org/10.3390/forecast4030040.
Texto completoLenin, Thingbaijam y N. Chandrasekaran. "Learning from Imbalanced Educational Data Using Ensemble Machine Learning Algorithms". Webology 18, Special Issue 01 (29 de abril de 2021): 183–95. http://dx.doi.org/10.14704/web/v18si01/web18053.
Texto completoArora, Madhur, Sanjay Agrawal y Ravindra Patel. "Machine Learning Technique for Predicting Location". International Journal of Electrical and Electronics Research 11, n.º 2 (30 de junio de 2023): 639–45. http://dx.doi.org/10.37391/ijeer.110254.
Texto completoRahimi, Nouf, Fathy Eassa y Lamiaa Elrefaei. "An Ensemble Machine Learning Technique for Functional Requirement Classification". Symmetry 12, n.º 10 (25 de septiembre de 2020): 1601. http://dx.doi.org/10.3390/sym12101601.
Texto completo., Hartono, Opim Salim Sitompul, Erna Budhiarti Nababan, Tulus ., Dahlan Abdullah y Ansari Saleh Ahmar. "A New Diversity Technique for Imbalance Learning Ensembles". International Journal of Engineering & Technology 7, n.º 2.14 (8 de abril de 2018): 478. http://dx.doi.org/10.14419/ijet.v7i2.11251.
Texto completoTeoh, Chin-Wei, Sin-Ban Ho, Khairi Shazwan Dollmat y Chuie-Hong Tan. "Ensemble-Learning Techniques for Predicting Student Performance on Video-Based Learning". International Journal of Information and Education Technology 12, n.º 8 (2022): 741–45. http://dx.doi.org/10.18178/ijiet.2022.12.8.1679.
Texto completoHussein, Salam Allawi, Alyaa Abduljawad Mahmood y Emaan Oudah Oraby. "Network Intrusion Detection System Using Ensemble Learning Approaches". Webology 18, SI05 (30 de octubre de 2021): 962–74. http://dx.doi.org/10.14704/web/v18si05/web18274.
Texto completoP A, Sadiyamole y Dr Manju Priya S. "Heart Disease Prediction Using Ensemble Stacking Technique". International Journal of Engineering Research in Computer Science and Engineering 9, n.º 8 (6 de agosto de 2022): 19–24. http://dx.doi.org/10.36647/ijercse/09.08.art004.
Texto completoZubair Khan, Mohammad. "Hybrid Ensemble Learning Technique for Software Defect Prediction". International Journal of Modern Education and Computer Science 12, n.º 1 (8 de febrero de 2020): 1–10. http://dx.doi.org/10.5815/ijmecs.2020.01.01.
Texto completoPandey, Hemakshi, Riya Goyal, Deepali Virmani y Charu Gupta. "Ensem_SLDR: Classification of Cybercrime using Ensemble Learning Technique". International Journal of Computer Network and Information Security 14, n.º 1 (8 de febrero de 2021): 81–90. http://dx.doi.org/10.5815/ijcnis.2022.01.07.
Texto completoAl Duhayyim, Mesfer, Sidra Abbas, Abdullah Al Hejaili, Natalia Kryvinska, Ahmad Almadhor y Uzma Ghulam Mohammad. "An Ensemble Machine Learning Technique for Stroke Prognosis". Computer Systems Science and Engineering 47, n.º 1 (2023): 413–29. http://dx.doi.org/10.32604/csse.2023.037127.
Texto completoChandra Jena, Prakash, Subhendu Kumar Pani y Debahuti Mishra. "A novel approach to ensemble learning in distributed data mining". International Journal of Engineering & Technology 7, n.º 3.3 (8 de junio de 2018): 233. http://dx.doi.org/10.14419/ijet.v7i2.33.14159.
Texto completoDhanwanth, Batini, Bandi Vivek, M. Abirami, Shaik Mohammad Waseem y Challapalli Manikantaa. "Forecasting Chronic Kidney Disease Using Ensemble Machine Learning Technique". International Journal on Recent and Innovation Trends in Computing and Communication 11, n.º 5s (1 de junio de 2023): 336–44. http://dx.doi.org/10.17762/ijritcc.v11i5s.7035.
Texto completoSun, Xiao Wei y Hong Bo Zhou. "Research on Applied Technology in Experiments with Three Boosting Algorithms". Advanced Materials Research 908 (marzo de 2014): 513–16. http://dx.doi.org/10.4028/www.scientific.net/amr.908.513.
Texto completoLiu, Rencheng, Saqib Ali, Syed Fakhar Bilal, Zareen Sakhawat, Azhar Imran, Abdullah Almuhaimeed, Abdulkareem Alzahrani y Guangmin Sun. "An Intelligent Hybrid Scheme for Customer Churn Prediction Integrating Clustering and Classification Algorithms". Applied Sciences 12, n.º 18 (18 de septiembre de 2022): 9355. http://dx.doi.org/10.3390/app12189355.
Texto completoShah, Shariq, Hossein Ghomeshi, Edlira Vakaj, Emmett Cooper y Rasheed Mohammad. "An Ensemble-Learning-Based Technique for Bimodal Sentiment Analysis". Big Data and Cognitive Computing 7, n.º 2 (30 de abril de 2023): 85. http://dx.doi.org/10.3390/bdcc7020085.
Texto completoVacchetti, Bartolomeo y Tania Cerquitelli. "Cinematographic Shot Classification with Deep Ensemble Learning". Electronics 11, n.º 10 (13 de mayo de 2022): 1570. http://dx.doi.org/10.3390/electronics11101570.
Texto completoCui, Su, Yiliang Han, Yifei Duan, Yu Li, Shuaishuai Zhu y Chaoyue Song. "A Two-Stage Voting-Boosting Technique for Ensemble Learning in Social Network Sentiment Classification". Entropy 25, n.º 4 (24 de marzo de 2023): 555. http://dx.doi.org/10.3390/e25040555.
Texto completoTroć, Maciej y Olgierd Unold. "Self-adaptation of parameters in a learning classifier system ensemble machine". International Journal of Applied Mathematics and Computer Science 20, n.º 1 (1 de marzo de 2010): 157–74. http://dx.doi.org/10.2478/v10006-010-0012-8.
Texto completoChandrasekar, Jayakumar, Surendar Madhawa y J. Sangeetha. "Data-driven disruption prediction in GOLEM Tokamak using ensemble classifiers". Journal of Intelligent & Fuzzy Systems 39, n.º 6 (4 de diciembre de 2020): 8365–76. http://dx.doi.org/10.3233/jifs-189155.
Texto completoRhmann, Wasiur. "An Ensemble of Hybrid Search-Based Algorithms for Software Effort Prediction". International Journal of Software Science and Computational Intelligence 13, n.º 3 (julio de 2021): 28–37. http://dx.doi.org/10.4018/ijssci.2021070103.
Texto completoLi, Xingjian, Haoyi Xiong, Zeyu Chen, Jun Huan, Cheng-Zhong Xu y Dejing Dou. "“In-Network Ensemble”: Deep Ensemble Learning with Diversified Knowledge Distillation". ACM Transactions on Intelligent Systems and Technology 12, n.º 5 (31 de octubre de 2021): 1–19. http://dx.doi.org/10.1145/3473464.
Texto completoAdamu, Yusuf Aliyu. "MALARIA PREDICTION MODEL USING ADVANCED ENSEMBLE MACHINE LEARNING TECHNIQUES". Journal of Medical pharmaceutical and allied sciences 10, n.º 6 (15 de diciembre de 2021): 3794–801. http://dx.doi.org/10.22270/jmpas.v10i6.1701.
Texto completoFerano, Francisco Calvin Arnel, Amalia Zahra y Gede Putra Kusuma. "Stacking ensemble learning for optical music recognition". Bulletin of Electrical Engineering and Informatics 12, n.º 5 (1 de octubre de 2023): 3095–104. http://dx.doi.org/10.11591/eei.v12i5.5129.
Texto completoChristianah, Abikoye Oluwakemi, Benjamin Aruwa Gyunka y Akande Noah Oluwatobi. "Optimizing Android Malware Detection Via Ensemble Learning". International Journal of Interactive Mobile Technologies (iJIM) 14, n.º 09 (17 de junio de 2020): 61. http://dx.doi.org/10.3991/ijim.v14i09.11548.
Texto completoMunsarif, Muhammad, Muhammad Sam’an y Safuan Safuan. "Peer to peer lending risk analysis based on embedded technique and stacking ensemble learning". Bulletin of Electrical Engineering and Informatics 11, n.º 6 (1 de diciembre de 2022): 3483–89. http://dx.doi.org/10.11591/eei.v11i6.3927.
Texto completoHamori, Hitoshi y Shigeyuki Hamori. "Does Ensemble Learning Always Lead to Better Forecasts?" Applied Economics and Finance 7, n.º 2 (12 de febrero de 2020): 51. http://dx.doi.org/10.11114/aef.v7i2.4716.
Texto completoMahajan, Palak, Shahadat Uddin, Farshid Hajati y Mohammad Ali Moni. "Ensemble Learning for Disease Prediction: A Review". Healthcare 11, n.º 12 (20 de junio de 2023): 1808. http://dx.doi.org/10.3390/healthcare11121808.
Texto completoSarkar, Nipa y Asha Rani Borah. "Predicting ESRD Risk via Supervised and Ensemble Machine Learning Technique". International Journal of Research in Advent Technology 7, n.º 4 (10 de abril de 2019): 173–77. http://dx.doi.org/10.32622/ijrat.74201970.
Texto completoLee, Yen-Hsien, Paul Jen-Hwa Hu, Tsang-Hsiang Cheng, Te-Chia Huang y Wei-Yao Chuang. "A preclustering-based ensemble learning technique for acute appendicitis diagnoses". Artificial Intelligence in Medicine 58, n.º 2 (junio de 2013): 115–24. http://dx.doi.org/10.1016/j.artmed.2013.03.007.
Texto completoAlruily, Meshrif, Sameh Abd El-Ghany, Ayman Mohamed Mostafa, Mohamed Ezz y A. A. Abd El-Aziz. "A-Tuning Ensemble Machine Learning Technique for Cerebral Stroke Prediction". Applied Sciences 13, n.º 8 (18 de abril de 2023): 5047. http://dx.doi.org/10.3390/app13085047.
Texto completoKrasnopolsky, Vladimir M. y Ying Lin. "A Neural Network Nonlinear Multimodel Ensemble to Improve Precipitation Forecasts over Continental US". Advances in Meteorology 2012 (2012): 1–11. http://dx.doi.org/10.1155/2012/649450.
Texto completoVerma, Pratibha, Vineet Kumar Awasthi y Sanat Kumar Sahu. "A Novel Design of Classification of Coronary Artery Disease Using Deep Learning and Data Mining Algorithms". Revue d'Intelligence Artificielle 35, n.º 3 (30 de junio de 2021): 209–15. http://dx.doi.org/10.18280/ria.350304.
Texto completoDevi, Debashree, Suyel Namasudra y Seifedine Kadry. "A Boosting-Aided Adaptive Cluster-Based Undersampling Approach for Treatment of Class Imbalance Problem". International Journal of Data Warehousing and Mining 16, n.º 3 (julio de 2020): 60–86. http://dx.doi.org/10.4018/ijdwm.2020070104.
Texto completoSalunkhe, Uma R. y Suresh N. Mali. "Security Enrichment in Intrusion Detection System Using Classifier Ensemble". Journal of Electrical and Computer Engineering 2017 (2017): 1–6. http://dx.doi.org/10.1155/2017/1794849.
Texto completoTsai, Chih-Fong y Chihli Hung. "Modeling credit scoring using neural network ensembles". Kybernetes 43, n.º 7 (29 de julio de 2014): 1114–23. http://dx.doi.org/10.1108/k-01-2014-0016.
Texto completoTang, Ling, Wei Dai, Lean Yu y Shouyang Wang. "A Novel CEEMD-Based EELM Ensemble Learning Paradigm for Crude Oil Price Forecasting". International Journal of Information Technology & Decision Making 14, n.º 01 (enero de 2015): 141–69. http://dx.doi.org/10.1142/s0219622015400015.
Texto completoAli, Abdullah Marish, Fuad A. Ghaleb, Bander Ali Saleh Al-Rimy, Fawaz Jaber Alsolami y Asif Irshad Khan. "Deep Ensemble Fake News Detection Model Using Sequential Deep Learning Technique". Sensors 22, n.º 18 (15 de septiembre de 2022): 6970. http://dx.doi.org/10.3390/s22186970.
Texto completoNamoun, Abdallah, Burhan Rashid Hussein, Ali Tufail, Ahmed Alrehaili, Toqeer Ali Syed y Oussama BenRhouma. "An Ensemble Learning Based Classification Approach for the Prediction of Household Solid Waste Generation". Sensors 22, n.º 9 (5 de mayo de 2022): 3506. http://dx.doi.org/10.3390/s22093506.
Texto completoLi, Kai y Hong Tao Gao. "A Subgraph-Based Selective Classifier Ensemble Algorithm". Advanced Materials Research 219-220 (marzo de 2011): 261–64. http://dx.doi.org/10.4028/www.scientific.net/amr.219-220.261.
Texto completoSrınıvasa Rao, B. "A New Ensenble Learning based Optimal Prediction Model for Cardiovascular Diseases". E3S Web of Conferences 309 (2021): 01007. http://dx.doi.org/10.1051/e3sconf/202130901007.
Texto completoHashim, Dhurgham Kadhim y Lamia Abed Noor Muhammed. "Performance of K-means algorithm based an ensemble learning". Bulletin of Electrical Engineering and Informatics 11, n.º 1 (1 de febrero de 2022): 575–80. http://dx.doi.org/10.11591/eei.v11i1.3550.
Texto completoLiu, Kun-Hong, Muchenxuan Tong, Shu-Tong Xie y Vincent To Yee Ng. "Genetic Programming Based Ensemble System for Microarray Data Classification". Computational and Mathematical Methods in Medicine 2015 (2015): 1–11. http://dx.doi.org/10.1155/2015/193406.
Texto completoAhmed, Kanwal, Muhammad Imran Nadeem, Dun Li, Zhiyun Zheng, Nouf Al-Kahtani, Hend Khalid Alkahtani, Samih M. Mostafa y Orken Mamyrbayev. "Contextually Enriched Meta-Learning Ensemble Model for Urdu Sentiment Analysis". Symmetry 15, n.º 3 (3 de marzo de 2023): 645. http://dx.doi.org/10.3390/sym15030645.
Texto completoAli, Muhammad Danish, Adnan Saleem, Hubaib Elahi, Muhammad Amir Khan, Muhammad Ijaz Khan, Muhammad Mateen Yaqoob, Umar Farooq Khattak y Amal Al-Rasheed. "Breast Cancer Classification through Meta-Learning Ensemble Technique Using Convolution Neural Networks". Diagnostics 13, n.º 13 (30 de junio de 2023): 2242. http://dx.doi.org/10.3390/diagnostics13132242.
Texto completoShamsuddin, Siti Nurasyikin, Noriszura Ismail y R. Nur-Firyal. "Life Insurance Prediction and Its Sustainability Using Machine Learning Approach". Sustainability 15, n.º 13 (7 de julio de 2023): 10737. http://dx.doi.org/10.3390/su151310737.
Texto completoTama, Bayu Adhi y Marco Comuzzi. "Leveraging a Heterogeneous Ensemble Learning for Outcome-Based Predictive Monitoring Using Business Process Event Logs". Electronics 11, n.º 16 (15 de agosto de 2022): 2548. http://dx.doi.org/10.3390/electronics11162548.
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