Hybrid decision tree and naïve Bayes classifiers for multi-class classification tasks DM Farid, L Zhang, CM Rahman, MA Hossain, R Strachan Expert systems with applications 41 (4), 1937-1946, 2014 | 497 | 2014 |
Feature selection and intrusion classification in NSL-KDD cup 99 dataset employing SVMs MS Pervez, DM Farid The 8th International Conference on Software, Knowledge, Information …, 2014 | 269 | 2014 |
Combining naive bayes and decision tree for adaptive intrusion detection DM Farid, N Harbi, MZ Rahman arXiv preprint arXiv:1005.4496, 2010 | 264 | 2010 |
An adaptive ensemble classifier for mining concept drifting data streams DM Farid, L Zhang, A Hossain, CM Rahman, R Strachan, G Sexton, ... Expert Systems with Applications 40 (15), 5895-5906, 2013 | 218 | 2013 |
Application of machine learning approaches in intrusion detection system: a survey NF Haq, AR Onik, MAK Hridoy, M Rafni, FM Shah, DM Farid IJARAI-International Journal of Advanced Research in Artificial Intelligence …, 2015 | 194 | 2015 |
Intelligent facial emotion recognition and semantic-based topic detection for a humanoid robot L Zhang, M Jiang, D Farid, MA Hossain Expert Systems with Applications 40 (13), 5160-5168, 2013 | 133 | 2013 |
Anomaly Network Intrusion Detection Based on Improved Self Adaptive Bayesian Algorithm. DM Farid, MZ Rahman J. Comput. 5 (1), 23-31, 2010 | 117 | 2010 |
Cusboost: Cluster-based under-sampling with boosting for imbalanced classification F Rayhan, S Ahmed, A Mahbub, R Jani, S Shatabda, DM Farid 2017 2nd international conference on computational systems and information …, 2017 | 111 | 2017 |
iDTI-ESBoost: identification of drug target interaction using evolutionary and structural features with boosting F Rayhan, S Ahmed, S Shatabda, DM Farid, Z Mousavian, A Dehzangi, ... Scientific reports 7 (1), 17731, 2017 | 110 | 2017 |
Adaptive intrusion detection based on boosting and naïve Bayesian classifier CM Rahman, DM Farid, MZ Rahman International Journal of Computer Applications, 2011 | 81 | 2011 |
Attacks classification in adaptive intrusion detection using decision tree CM Rahman, DM Farid, N Harbi, E Bahri, MZ Rahman World Academy of Science, Engineering and Technology, 2010 | 69 | 2010 |
An adaptive rule-based classifier for mining big biological data DM Farid, MA Al-Mamun, B Manderick, A Nowe Expert Systems with Applications 64, 305-316, 2016 | 66 | 2016 |
Adaptive network intrusion detection learning: attribute selection and classification DM Farid, J Darmont, N Harbi, HH Nguyen, MZ Rahman International Conference on computer systems Engineering (ICCSE 2009), TH60000, 2009 | 55 | 2009 |
FRnet-DTI: Deep convolutional neural network for drug-target interaction prediction F Rayhan, S Ahmed, Z Mousavian, DM Farid, S Shatabda Heliyon 6 (3), 2020 | 54 | 2020 |
Effective DNA binding protein prediction by using key features via Chou’s general PseAAC S Adilina, DM Farid, S Shatabda Journal of theoretical biology 460, 64-78, 2019 | 54 | 2019 |
Improving detection accuracy for imbalanced network intrusion classification using cluster-based under-sampling with random forests MO Miah, SS Khan, S Shatabda, DM Farid 2019 1st international conference on advances in science, engineering and …, 2019 | 51 | 2019 |
The prediction of traffic flow with regression analysis I Alam, DM Farid, RJF Rossetti Emerging Technologies in Data Mining and Information Security: Proceedings …, 2019 | 51 | 2019 |
Hybrid methods for class imbalance learning employing bagging with sampling techniques S Ahmed, A Mahbub, F Rayhan, R Jani, S Shatabda, DM Farid 2017 2nd International Conference on Computational Systems and Information …, 2017 | 51 | 2017 |
Mining complex data streams: discretization, attribute selection and classification DM Farid, CM Rahman Journal of Advances in Information Technology 4 (3), 129-135, 2013 | 45 | 2013 |
Novel class detection in concept-drifting data stream mining employing decision tree DM Farid, CM Rahman 2012 7th international conference on electrical and computer engineering …, 2012 | 42 | 2012 |