Bagging predictors
Breiman, Leo·1996·Machine Learning
Cited by (228)
Items 201–228 of 228
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- Cross-Diagnosis Structural Correlates of Autistic-Like Social Communication DifferencesKushki, Azadeh, Cardy, Robyn E, Panahandeh, Sina, Malihi, Mahan, Hammill, Christopher, Brian, Jessica, Iaboni, Alana, Taylor, Margot J, Schachar, Russell, Crosbie, Jennifer et al. · 2021 · Cerebral Cortex
- P300 event-related potential detection using one-dimensional convolutional capsule networksLiu, Xiang, Xie, Qingsheng, Lv, Jian, Huang, Haisong, Wang, Weixing · 2021 · Expert Systems with Applications
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- Age-related differences in cerebral blood flow and cortical thickness with an application to age predictionMacDonald, M. Ethan, Williams, Rebecca J., Rajashekar, Deepthi, Stafford, Randall B., Hanganu, Alexadru, Sun, Hongfu, Berman, Avery J.L., McCreary, Cheryl R., Frayne, Richard, Forkert, Nils D. et al. · 2020 · Neurobiology of Aging
- An ensemble learning strategy for panel time series forecasting of excess mortality during the COVID-19 pandemicAshofteh, Afshin, Bravo, Jorge M., Ayuso, Mercedes · 2022 · Applied Soft Computing
- Variable time delay estimation in continuous industrial processesCattaldo, Marco, Ferrer, Alberto, Måge, Ingrid · 2024 · Chemometrics and Intelligent Laboratory Systems
- QASC: A Dataset for Question Answering via Sentence CompositionKhot, Tushar, Clark, Peter, Guerquin, Michal, Jansen, Peter, Sabharwal, Ashish · 2020 · Proceedings of the AAAI Conference on Artificial Intelligence
- Artificial Neural Networks Classification of Patients with Parkinsonism based on GaitFernandes, Carlos, Fonseca, Luis, Ferreira, Flora, Gago, Miguel, Costa, Lus, Sousa, Nuno, Ferreira, Carlos, Gama, Joao, Erlhagen, Wolfram, Bicho, Estela · 2018 · 2018 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)
- A soft sensor for simulating algal cell density based on dynamic response to environmental changes in a eutrophic shallow lakeRao, Wenxin, Qian, Xin, Fan, Yifan, Liu, Tong · 2023 · Science of The Total Environment
- Counteracting the contemporaneous proliferation of digital forgeries and fake newsFERREIRA, ALEXANDRE, CARVALHO, TIAGO, ANDALÓ, FERNANDA, ROCHA, ANDERSON · 2019 · Anais da Academia Brasileira de Ciências
- Quantum computing and supervised machine learningOneto, L., Ridella, S., Anguita, D. · 2017 · Quantum Inspired Computational Intelligence
- Machine-learnt versus analytical models of TCP throughputEl Khayat, I., Geurts, P., Leduc, G. · 2007 · Computer Networks
- Exploiting Data and Human Knowledge for Predicting Wildlife PoachingGurumurthy, Swaminathan, Yu, Lantao, Zhang, Chenyan, Jin, Yongchao, Li, Weiping, Zhang, Xiaodong, Fang, Fei · 2018 · Proceedings of the 1st ACM SIGCAS Conference on Computing and Sustainable Societies
- Modeling health risks using neural network ensemblesSmith, Brandon M., Criminisi, Antonio, Sorek, Noam, Harari, Yaar, Sood, Neeraj, Heymsfield, Steven B. · 2024 · PLOS ONE
- Engineering the Neural Automatic Passenger CounterJahn, Nico, Siebert, Michael · 2022 · Engineering Applications of Artificial Intelligence
- Intelligence plays dice: Stochasticity is essential for machine learningSabuncu, Mert R. · 2020 · arXiv
- TIPS: A Prompt Engineering Framework for Code Classification and Generation on Resource-Constrained SystemsChen, Wei-Cheng, Chen, Shih-Yeh · 2026 · IEEE Access