The Strength of Weak Learnability

Cited by (1,455)

Items 1,201–1,300 of 1,455

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3. Boosting support vector regression in QSAR studies of bioactivities of chemical compounds
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15. Algorithm selection on a meta level
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16. Subcellular Localization Prediction through Boosting Association Rules
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17. Kernel Classifier Construction Using Orthogonal Forward Selection and Boosting With Fisher Ratio Class Separability Measure
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18. Evolving meta-ensemble of classifiers for handling incomplete and unbalanced datasets in the cyber security domain
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19. Machinery fault diagnosis using joint global and local/nonlocal discriminant analysis with selective ensemble learning
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20. Study of ensemble learning-based fusion prognostics
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21. General Bounds on Statistical Query Learning and PAC Learning with Noise via Hypothesis Boosting
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22. A two‐stage forecasting approach for short‐term intermodal freight prediction
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23. Comparing modern and traditional modeling methods for predicting soil moisture in IoT-based irrigation systems
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24. Transfer learning-based confinement strength prediction of concrete confined by FRP transverse reinforcements
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25. Mapping and modeling groundwater potential using machine learning, deep learning and ensemble learning models in the Saiss basin (Fez-Meknes region, Morocco)
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26. Soft computing models for prediction of bentonite plastic concrete strength
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28. Multiobjective genetic classifier selection for random oracles fuzzy rule-based classifier ensembles: How beneficial is the additional diversity?
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29. A Double Pruning Scheme for Boosting Ensembles
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30. Classification models for the prediction of clinicians’ information needs
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31. Modeling Merging Acceleration and Deceleration Behavior Based on Gradient-Boosting Decision Tree
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32. Machine Learning Methods for the Prediction of the Inclusion Content of Clean Steel Fabricated by Electric Arc Furnace and Rolling
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34. Mass appraisal as affordable public policy: Open data and machine learning for mapping urban land values
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35. A Machine Learning Approach for Predicting the Maximum Spreading Factor of Droplets upon Impact on Surfaces with Various Wettabilities
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36. NP-Hardness of Learning Programs and Partial MCSP
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37. A Weighted Stacking Ensemble Model With Sampling for Fake Reviews Detection
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38. Boosting GARCH and neural networks for the prediction of heteroskedastic time series
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39. Ensemble SVR for prediction of time series
    Yufeng Deng, Xing Jin, Yixin Zhong · 2005 · International Conference on Machine Learning and Cybernetics
40. Large Earthquake Magnitude Prediction in Chile with Imbalanced Classifiers and Ensemble Learning
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41. Multi-label classification of member participation in online innovation communities
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42. An imprecise deep forest for classification
    Lev Vladimirovich Utkin · 2019 · Expert Systems with Applications
43. An Epicurean learning approach to gene-expression data classification
    Andreas A. Albrecht, Staal A. Vinterbo, Lucila Ohno-machado A · 2003 · Artificial Intelligence in Medicine
44. Bayesian brains and cognitive mechanisms:
    Henry Brighton, Gerd Gigerenzer · 2008
45. NOW G-Net: learning classification programs on networks of workstations
    Cosimo Anglano, Marco Botta · 2002 · IEEE Transactions on Evolutionary Computation
46. Comparing pure parallel ensemble creation techniques against bagging
    Lawrence Hall, Kevin W. Bowyer, Robert E. Banfield, Divya Bhadoria, W. Philip Kegelmeyer, Steven A. Eschrich · 2004 · Proceedings
47. Understanding Machine Learning Principles: Learning, Inference, Generalization, and Computational Learning Theory
    Ke-Lin Du, Rengong Zhang, Bingchun Jiang, Jie Zeng, Jiabin Lu · 2025 · Mathematics
48. An effective ensemble pruning algorithm based on frequent patterns
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49. An ensemble method for unbalanced sentiment classification
    Dongmei Zhang, Jun Ma, Yi Jing, Xiaofei Niu, Xiaojing Xu · 2015 · International Conference on Natural Computation (ICNC)
50. Object-Based Ensemble Learning for Pan-European Riverscape Units Mapping Based on Copernicus VHR and EU-DEM Data Fusion
    Luca Demarchi, W. van de Bund, A. Pistocchi · 2020 · Remote Sensing
51. CS-AF: A cost-sensitive multi-classifier active fusion framework for skin lesion classification
    Di Zhuang, Keyu Chen, J. Morris Chang · 2022 · Neurocomputing
52. Combined climate and regional mosquito habitat model based on machine learning
    Ralf Wieland, Katrin Kuhls, Hartmut H. K. Lentz, Franz J. Conraths, Helge Kampen, Doreen Werner · 2021 · Ecological Modelling
53. BurnoutEnsemble: Augmented Intelligence to Detect Indications for Burnout in Clinical Psychology
    Ghofrane Merhbene, Sukanya Nath, Alexandre R. Puttick, Mascha Kurpicz-Briki · 2022 · Frontiers in Big Data
54. Short-Term Load Forecasting Based on Multi-Scale Ensemble Deep Learning Neural Network
    Qin Shen, Li Mo, Guanjun Liu, Jianzhong Zhou, Yongchuan Zhang, Pinan Ren · 2023 · IEEE Access
55. Maximizing power density in proton exchange membrane fuel cells: An integrated optimization framework coupling multi-physics structure models, machine learning, and improved gray wolf optimizer
    Hong-Wei Li, Lei Wang, Jun-Nan Liu, Yue Yang, Guolong Lu · 2023 · Fuel
56. Committee neural networks with fuzzy genetic algorithm
    S. A. Jafari, Syamsiah Mashohor, Mohammad Jalali Varnamkhasti · 2011 · Journal of Petroleum Science and Engineering
57. A design framework for hierarchical ensemble of multiple feature extractors and multiple classifiers
    Kyounghoon Kim, Helin Lin, Jin Young Choi, Ki‐Young Choi · 2015 · Pattern Recognition
58. EPRENNID: An evolutionary prototype reduction based ensemble for nearest neighbor classification of imbalanced data
    Sarah Vluymans, Isaac Triguero A, Chris Cornelis A, Yvan Saeys · 2016 · Neurocomputing
59. Formulating Ensemble Learning of SVMs Into a Single SVM Formulation by Negative Agreement Learning
    Jie Zhou, Zhibin Jiang, Fu-Lai Chung, Shitong Wang · 2020 · IEEE Transactions on Systems Man and Cybernetics Systems
60. Novel and robust machine learning model to optimize biodiesel production from algal oil using CaO and CaO/Al2O3 as catalyst: Sustainable green energy
    Yan Liu, Biju Theruvil Sayed, Ramaswamy Sivaraman, Saad M. Alshahrani, Kumar Venkatesan, Kamal Y. Thajudeen, Mohammed Al‐Bahrani, Salema K. Hadrawi, Ghulam Yasin · 2023 · Environmental Technology & Innovation
61. Introduction to SVM
    Hadi Veisi · 2023 · Industrial and applied mathematics
62. Prediction of shear strength of RC slender beams based on interpretable machine learning
    Cailong Ma, Wenhu Wang, Sixuan Wang, Zheyi Guo, Xinlong Feng · 2023 · Structures
63. Hybrid PSO with tree-based models for predicting uniaxial compressive strength and elastic modulus of rock samples
    Niaz Muhammad Shahani, Qin Xiaowei, Xin Wei, Jun Li, Tuerhong Aizitiliwumaier, Xiaohu Ma, Qiu Shigui, Cao Weikang, Liu Longhe · 2024 · Frontiers in Earth Science
64. Machine learning optimization of operating parameters to achieve high power density and efficiency of polymer electrolyte membrane fuel cell
    Rashed Kaiser, Jong-Chun Park · 2024 · Chemical Engineering Science
65. XEMLPD: an explainable ensemble machine learning approach for Parkinson disease diagnosis with optimized features
    Fahmida Khanom, S. K. Biswas, Mohammad Shorif Uddin, Rafid Mostafiz · 2024 · International Journal of Speech Technology
66. Face detection and recognition in an unconstrained environment for mobile visual assistive system
    Shonal Chaudhry, Rohitash Chandra · 2016 · Applied Soft Computing
67. Homogeneous and heterogeneous ensemble classification methods in diabetes disease: a review
    José Luis Fernández‐Alemán, Juan Manuel Carrillo de Gea, Mohamed Hosni, Ali Idri, Ginés Garcı́a-Mateos · 2019 · Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)
68. A multi-model ensemble approach for the assessment of climatic and anthropogenic impacts on river flow change
    Seyedehshima Pooralihossein, Majid Delavar · 2019 · Hydrological Sciences Journal
69. Machine Learning
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70. Neural ordinary differential equations with irregular and noisy data
    Pawan Goyal, Peter Benner · 2023 · Royal Society Open Science
71. Financial fraud detection by using Grammar-based multi-objective genetic programming with ensemble learning
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72. Predicting adequacy of vancomycin regimens: A learning-based classification approach to improving clinical decision making
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73. NB+: An improved Naïve Bayesian algorithm
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74. A model-free Bayesian classifier
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75. People Counting by Dense WiFi MIMO Networks: Channel Features and Machine Learning Algorithms
    Sanaz Kianoush, Stefano Savazzi, Vittorio Rampa, Monica Nicoli · 2019 · Sensors
76. Specification and Simulation of Statistical Query Algorithms for Efficiency and Noise Tolerance
    Javed Alexander Aslam, Scott Evan Decatur · 1998 · Journal of Computer and System Sciences
77. Symbolic regression for strength prediction of eccentrically loaded concrete-filled steel tubular columns
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78. Ensemble fuzzy models in personalized medicine: Application to vasopressors administration
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79. An effective semi-cross-validation model selection method for extreme learning machine with ridge regression
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80. Software quality assessment using a multi-strategy classifier
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81. Boosted random contextual semantic space based representation for visual recognition
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82. An optimized multi-classifiers ensemble learning for identification of ginsengs based on electronic nose
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83. Constraint learning based gradient boosting trees
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84. Evaluation Of Selected Meta Learning Algorithms For The Prediction Improvement Of Network Intrusion Detection System
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85. Discrimination between wild-grown and cultivated Gastrodia elata by near-infrared spectroscopy and chemometrics
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86. Ensemble Learning via Higher Order Singular Value Decomposition for Integrating Data and Classifier Fusion in Water Quality Monitoring
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87. A Method of Enterprise Financial Risk Analysis and Early Warning Based on Decision Tree Model
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88. Adaptive Dense Ensemble Model for Text Classification
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89. Optimal Causal Decision Trees Ensemble for Improved Prediction and Causal Inference
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92. Boosting the Federation: Cross-Silo Federated Learning without Gradient Descent
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93. Fusion-based machine learning approach for classification of algae varieties exposed to different light sources in the growth stage
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94. Intelligent cryptocurrency trading system using integrated AdaBoost-LSTM with market turbulence knowledge
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95. An ensemble approach of dual base learners for multi-class classification problems
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96. Facial Expression Recognition Based on t-SNE and AdaboostM2
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97. Machine Learning: The State of the Art
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98. A robust ensemble of neuro-fuzzy classifiers for DDoS attack detection
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99. Improved Vine Copula-Based Dependence Description for Multivariate Process Monitoring Based on Ensemble Learning
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100. Integrating Qualitative Comparative Analysis and Support Vector Machine Methods to Reduce Passengers’ Resistance to Biometric E-Gates for Sustainable Airport Operations
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