The Strength of Weak Learnability

Cited by (1,455)

Items 801–900 of 1,455

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2. Link Adaptation on an Underwater Communications Network Using Machine Learning Algorithms: Boosted Regression Tree Approach
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3. An improved random forest algorithm and its application to wind pressure prediction
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4. Meta-Learning to Improve Unsupervised Intrusion Detection in Cyber-Physical Systems
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5. HSDLM
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6. Clustering-based selective neural network ensemble
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7. A particle swarm optimization based ensemble for vegetable crop disease recognition
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8. Meta-Health Stack: A new approach for breast cancer prediction
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9. Probabilistic machine learning approach to predict incompetent rock masses in TBM construction
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10. Robust and interpretable AI-guided marker for early dementia prediction in real-world clinical settings
    Liz Yuanxi Lee, Delshad Vaghari, Michael C. Burkhart, Peter Tiňo B, Marcella Montagnese, Zhuoyu Li, Katharina Zühlsdorff, Joseph Giorgio, Guy B. Williams, Eddie Jun Yi Chong et al. · 2024 · EClinicalMedicine
11. Some Analysis and Research of the AdaBoost Algorithm
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12. Robust Object Classification in Underwater Sidescan Sonar Images by Using Reliability-Aware Fusion of Shadow Features
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13. Sparse Kernel-Based Hyperspectral Anomaly Detection
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14. Tuning the ensemble selection process of schema matchers
    Avigdor Gal, Tomer Sagi · 2010 · Information Systems
15. On the Importance of Data Balancing for Symbolic Regression
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16. Conformal Prediction Using Decision Trees
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17. Background subtraction in varying illuminations using an ensemble based on an enlarged feature set
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18. A Semiautomated Probabilistic Framework for Tree-Cover Delineation From 1-m NAIP Imagery Using a High-Performance Computing Architecture
    Saikat Basu, Sangram Ganguly, Ramakrishna Nemani, Supratik Mukhopadhyay, Gong Zhang, CRISTINA MILESI, Andrew Michaelis, Petr Votava, Ralph Dubayah, Laura Innice Duncanson et al. · 2015 · IEEE Transactions on Geoscience and Remote Sensing
19. Automated sperm morphology analysis approach using a directional masking technique
    H. Ilhan, Gorkem Serbes, N. Aydin · 2020 · Comput. Biol. Medicine
20. Anomalies Prediction in Radon Time Series for Earthquake Likelihood Using Machine Learning-Based Ensemble Model
    Adil Aslam Mir, Fatih V. Çelebi, Hadeel Alsolai, Shahzad Ahmad Qureshi, Muhammad Rafique, Jaber S. Alzahrani, Hany Mahgoub, Manar Ahmed Hamza · 2022 · IEEE Access
21. Extreme Learning Machine Ensemble Using Bagging for Facial Expression Recognition
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22. Determination of nicotine in tobacco samples by near-infrared spectroscopy and boosting partial least squares
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23. CinC challenge — Assessing the usability of ECG by ensemble decision trees
    Sebastian Zaunseder, Robert Huhle, Hagen Malberg · 2011 · OPUS (Augsburg University)
24. Sample Compression Schemes for VC Classes
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25. A Supervised Approach to Arabic Text Summarization Using AdaBoost
    Riadh Belkebir, Ahmed Guessoum · 2015 · Advances in intelligent systems and computing
26. A New Imbalanced Learning and Dictions Tree Method for Breast Cancer Diagnosis
    Hamïd Parvïn, Behrouz Minaei Bidgoli, Hamid Alinejad‐Rokny · 2013 · Journal of Bionanoscience
27. Constructing Web User Profiles: A Non-invasive Learning Approach
    Philip K. Chan · 2000 · Lecture notes in computer science
28. Specification and simulation of statistical query algorithms for efficiency and noise tolerance
    Javed Alexander Aslam, Scott Evan Decatur · 1995 · Conference on Learning Theory
29. MultiStage Cascading of Multiple Classifiers: One Man's Noise is Another Man's Data
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30. Applying Boosting Techniques to Genetic Programming
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31. Fast data selection for SVM training using ensemble margin
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32. Prediction for Manufacturing Factors in a Steel Plate Rolling Smart Factory Using Data Clustering-Based Machine Learning
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33. Vulnerable road users’ crash hotspot identification on multi-lane arterial roads using estimated exposure and considering context classification
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34. Decimated input ensembles for improved generalization
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35. Collective-agreement-based pruning of ensembles
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36. Incremental Activity Modeling and Recognition in Streaming Videos
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37. Bootstrapping Boosted Random Ferns for discriminative and efficient object classification
    Michael Villamizar, Juan Andrade‐Cetto, Alberto Sanfeliu, Francesc Moreno-Noguer · 2012 · Pattern Recognition
38. Touch modality interpretation for an EIT-based sensitive skin
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39. Understanding survey-based inflation expectations
    Travis J. Berge · 2018 · International Journal of Forecasting
40. MRI white matter lesion segmentation using an ensemble of neural networks and overcomplete patch-based voting
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41. A hybrid ensemble learning method for tourist route recommendations based on geo-tagged social networks
    Lin Wan, Yuming Hong, Zhou Huang, Xia Peng, Ran Li · 2018 · International Journal of Geographical Information Systems
42. SSEM: A Novel Self-Adaptive Stacking Ensemble Model for Classification
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43. Novel weighted ensemble classifier for smartphone based indoor localization
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44. Toward Robust Early-Warning Models: A Horse Race, Ensembles and Model Uncertainty
    Markus Holopainen, Peter Sarlin · 2015 · SSRN Electronic Journal
45. IMPROVED ADAPTIVE SPLITTING AND SELECTION: THE HYBRID TRAINING METHOD OF A CLASSIFIER BASED ON A FEATURE SPACE PARTITIONING
    Konrad Jackowski, Bartosz Krawczyk, Michał Woźniak · 2014 · International Journal of Neural Systems
46. Algorithms going wild – A review of machine learning techniques for terrestrial ecology
    Cristina Cipriano, Sergio Noce, Simone Mereu, Monia Santini · 2025 · Ecological Modelling
47. A review and experimental study on the application of classifiers and evolutionary algorithms in EEG-based brain–machine interface systems
    Farajollah Tahernezhad-Javazm, Vahid Azimirad, Maryam Shoaran · 2017 · Journal of Neural Engineering
48. Theoretical and Practical Model Selection Methods for Support Vector Classifiers
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49. Minimally overfitted learners: A general framework for ensemble learning
    Víctor Aceña, Isaac Martín de Diego, Rubén R. Fernández, Javier M. Moguerza · 2022 · Knowledge-Based Systems
50. Bagging and Boosting statistical machine translation systems
    Tong Xiao, Jingbo Zhu, Tongran Liu · 2012 · Artificial Intelligence
51. Meta-ELM: ELM with ELM hidden nodes
    Shizhong Liao, Chang Feng · 2013 · Neurocomputing
52. Software effort estimation based on open source projects: Case study of Github
    Fumin Qi, Xiao‐Yuan Jing, Xiaoke Zhu, Xiaoyuan Xie, Baowen Xu, Shi Ying · 2017 · Information and Software Technology
53. On the Optimal Size of Candidate Feature Set in Random forest
    Sunwoo Han, Hyunjoong Kim · 2019 · Applied Sciences
54. Forecasting corporate failure using ensemble of self-organizing neural networks
    Philippe du Jardin · 2020 · European Journal of Operational Research
55. Energy-Efficient Information-Driven Coverage for Physical Movement Monitoring in Body Sensor Networks
    Hassan G Ghasemzadeh, Eric Guenterberg, Roozbeh Jafari · 2009 · IEEE Journal on Selected Areas in Communications
56. A Review on Feature Selection and Ensemble Techniques for Intrusion Detection System
    Majid Torabi, Nur Izura Udzir, Mohd Taufik Abdullah, Razali Yaakob · 2021 · International Journal of Advanced Computer Science and Applications
57. A new method for hierarchical clustering combination
    Abdolreza Mirzaei, Mohammad Rahmati, Majid A. Ahmadi · 2008 · Intelligent Data Analysis
58. MCBoost: Multiple Classifier Boosting for Perceptual Co-clustering of Images and Visual Features
    Tae‐Kyun Kim, Roberto Cipolla, , · 2009
59. Ensemble learning based on approximate reducts and bootstrap sampling
    Feng Xian Jiang, Xu Yu, Junwei Du, Dunwei Gong, Youqiang Zhang, Yanjun Peng · 2020 · Information Sciences
60. Machine Learning Risk Prediction Model of 90-day Mortality After Gastrectomy for Cancer
    Manuel Pera, Joan Gibert, Marta Gimeno, Elisenda Garsot, Emma Eizaguirre, Mònica Miró, Sandra Castro, Coro Miranda, Lorena Reka, Saioa Leturio et al. · 2022 · Annals of Surgery
61. Machine learning strategies for small sample size in materials science
    Qiuling Tao, Jinxin Yu, Xiangyu Mu, Xue Jia, Rongpei Shi, Zhifu Yao, Cuiping Wang, Haijun Zhang, Xingjun Liu · 2025 · Science China Materials
62. Two applications of the LSA machine
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63. Greedy optimization classifiers ensemble based on diversity
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64. Real-time recognition of surgical tasks in eye surgery videos
    Gwenolé Quellec, Katia Charrière, Mathieu Lamard, Zakarya Droueche, Christian Roux, Béatrice Cochener, Guy Cazuguel · 2014 · Medical Image Analysis
65. A novel classifier ensemble method with sparsity and diversity
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66. Convex ensemble learning with sparsity and diversity
    Xu-Cheng Yin, Kaizhu Huang, Chun Hung Yang, Hongwei Hao · 2014 · Information Fusion
67. A Genetic Fuzzy Linguistic Combination Method for Fuzzy Rule-Based Multiclassifiers
    Krzysztof Trawiński, Óscar Cordón, Luciano Sánchez, Arnaud Quirin · 2013 · IEEE Transactions on Fuzzy Systems
68. New Ensemble Machine Learning Method for Classification and Prediction on Gene Expression Data
    Ching‐Wei Wang · 2006 · Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)
69. Ensemble learning from ensemble docking: revisiting the optimum ensemble size problem
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70. Investigations of bagged kernel partial least squares (KPLS) and boosting KPLS with applications to near‐infrared (NIR) spectra
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71. An efficient modified boosting method for solving classification problems
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72. Boosting by weighting critical and erroneous samples
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73. Boosting and hard-core sets
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74. Performance and efficiency: recent advances in supervised learning
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75. Hybrid modeling for the prediction of leaching rate in leaching process based on negative correlation learning bagging ensemble algorithm
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76. Learning rich semantics from news video archives by style analysis
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77. Bridging Local and Global Data Cleansing: Identifying Class Noise in Large, Distributed Data Datasets
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78. Negative correlation in incremental learning
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79. Blockage Intelligence in Complex Environments for Beyond 5G Localization
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80. Empirical analysis and evaluation of approximate techniques for pruning regression bagging ensembles
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81. An evolutionary programming based asymmetric weighted least squares support vector machine ensemble learning methodology for software repository mining
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82. Multi-scale Conditional Random Fields for first-person activity recognition on elders and disabled patients
    Kai Zhan, Steven G. Faux, Fabio Tozeto Ramos · 2014 · Pervasive and Mobile Computing
83. A neural network ensemble model for on-line monitoring of process mean and variance shifts in correlated processes
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84. Robust Statistical Fusion of Image Labels
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85. Can-CSC-GBE: Developing Cost-sensitive Classifier with Gentleboost Ensemble for breast cancer classification using protein amino acids and imbalanced data
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86. Ensemble Learning for Overall Power Conversion Efficiency of the All-Organic Dye-Sensitized Solar Cells
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87. Machine learning algorithms for the prediction of non-metallic inclusions in steel wires for tire reinforcement
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88. Topic classification of electric vehicle consumer experiences with transformer-based deep learning
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89. Stochastic configuration network ensembles with selective base models
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90. Incremental Learning of Boosted Face Detector
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91. Training Distributed GP Ensemble With a Selective Algorithm Based on Clustering and Pruning for Pattern Classification
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92. A survey of neural network ensembles
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93. Estimating relatedness via data compression
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94. Regression Trees and Rule-Based Models
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95. Navigation made personal
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96. Forecasting bankruptcy using biclustering and neural network-based ensembles
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97. Asymmetric bagging and feature selection for activities prediction of drug molecules
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98. ARIMA-AdaBoost hybrid approach for product quality prediction in advanced transformer manufacturing
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99. Predicting seepage losses from lined irrigation canals using machine learning models
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100. Small Target-YOLOv5: Enhancing the Algorithm for Small Object Detection in Drone Aerial Imagery Based on YOLOv5
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