Semi-supervised self-training for decision tree classifiers J Tanha, M Van Someren, H Afsarmanesh International Journal of Machine Learning and Cybernetics 8, 355-370, 2017 | 312 | 2017 |
Boosting methods for multi-class imbalanced data classification: an experimental review J Tanha, Y Abdi, N Samadi, N Razzaghi, M Asadpour Journal of Big Data 7 (1), 1-47, 2020 | 286 | 2020 |
The role of collaborative networks in sustainability LM Camarinha-Matos, H Afsarmanesh, X Boucher Collaborative Networks for a Sustainable World: 11th IFIP WG 5.5 Working …, 2010 | 110 | 2010 |
COVID-19 infection forecasting based on deep learning in Iran M Azarafza, M Azarafza, J Tanha MedRxiv, 2020.05. 16.20104182, 2020 | 57 | 2020 |
Boosting for multiclass semi-supervised learning J Tanha, M Van Someren, H Afsarmanesh Pattern Recognition Letters 37, 63-77, 2014 | 32 | 2014 |
Tune your brown clustering, please L Derczynski, S Chester, KS Bøgh International Conference Recent Advances in Natural Language Processing …, 2015 | 31 | 2015 |
Combination of ant colony optimization and Bayesian classification for feature selection in a bioinformatics dataset MH Aghdam, J Tanha, AR Naghsh-Nilchi, ME Basiri Journal of Computer Science & Systems Biology 2 (3), 186-199, 2009 | 28 | 2009 |
Disagreement-based co-training J Tanha, M van Someren, H Afsarmanesh 2011 IEEE 23rd international conference on tools with artificial …, 2011 | 27 | 2011 |
Relationship among prognostic indices of breast cancer using classification techniques J Tanha, H Salarabadi, M Aznab, A Farahi, M Zoberi Informatics in Medicine Unlocked 18, 100265, 2020 | 22 | 2020 |
Multiclass semi-supervised learning for animal behavior recognition from accelerometer data J Tanha, M Van Someren, M de Bakker, W Bouteny, ... 2012 IEEE 24th International Conference on Tools with Artificial …, 2012 | 22 | 2012 |
CPSSDS: conformal prediction for semi-supervised classification on data streams J Tanha, N Samadi, Y Abdi, N Razzaghi-Asl Information Sciences 584, 212-234, 2022 | 21 | 2022 |
MSSBoost: A new multiclass boosting to semi-supervised learning J Tanha Neurocomputing 314, 251-266, 2018 | 21 | 2018 |
An adaboost algorithm for multiclass semi-supervised learning J Tanha, M van Someren, H Afsarmanesh 2012 IEEE 12th International Conference on Data Mining, 1116-1121, 2012 | 21 | 2012 |
STDS: self-training data streams for mining limited labeled data in non-stationary environment S Khezri, J Tanha, A Ahmadi, A Sharifi Applied Intelligence 50, 1448-1467, 2020 | 19 | 2020 |
COVID‐19 Detection Using Deep Convolutional Neural Networks and Binary Differential Algorithm‐Based Feature Selection from X‐Ray Images MS Iraji, MR Feizi-Derakhshi, J Tanha Complexity 2021 (1), 9973277, 2021 | 18 | 2021 |
A novel semi-supervised ensemble algorithm using a performance-based selection metric to non-stationary data streams S Khezri, J Tanha, A Ahmadi, A Sharifi Neurocomputing 442, 125-145, 2021 | 17 | 2021 |
A selection metric for semi-supervised learning based on neighborhood construction M Emadi, J Tanha, ME Shiri, MH Aghdam Information Processing & Management 58 (2), 102444, 2021 | 15 | 2021 |
A multiclass boosting algorithm to labeled and unlabeled data J Tanha International Journal of Machine Learning and Cybernetics 10 (12), 3647-3665, 2019 | 15 | 2019 |
Ensemble approaches to semi-supervised learning J Tanha SIKS, 2013 | 13 | 2013 |
AMTLDC: a new adversarial multi-source transfer learning framework to diagnosis of COVID-19 H Alhares, J Tanha, MA Balafar Evolving Systems 14 (6), 1101-1115, 2023 | 10 | 2023 |