Natthakan Iam-On
Natthakan Iam-On
Lecturer of Computer Science, Aberystwyth University
Verified email at
Cited by
Cited by
A link-based approach to the cluster ensemble problem
N Iam-On, T Boongoen, S Garrett, C Price
IEEE transactions on pattern analysis and machine intelligence 33 (12), 2396 …, 2011
Cluster ensembles: A survey of approaches with recent extensions and applications
T Boongoen, N Iam-On
Computer Science Review 28, 1-25, 2018
A link-based cluster ensemble approach for categorical data clustering
N Iam-On, T Boongeon, S Garrett, C Price
IEEE Transactions on knowledge and data engineering 24 (3), 413-425, 2010
LCE: a link-based cluster ensemble method for improved gene expression data analysis
N Iam-On, T Boongoen, S Garrett
Bioinformatics 26 (12), 1513-1519, 2010
Refining pairwise similarity matrix for cluster ensemble problem with cluster relations
N Iam-On, T Boongoen, S Garrett
Discovery Science: 11th International Conference, DS 2008, Budapest, Hungary …, 2008
Linkclue: A matlab package for link-based cluster ensembles
N Iam-On, S Garrett
Journal of Statistical Software 36, 1-36, 2010
Extending data reliability measure to a filter approach for soft subspace clustering
T Boongoen, C Shang, N Iam-On, Q Shen
IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics) 41 …, 2011
Improved student dropout prediction in Thai University using ensemble of mixed-type data clusterings
N Iam-On, T Boongoen
International Journal of Machine Learning and Cybernetics 8, 497-510, 2017
Generating descriptive model for student dropout: a review of clustering approach
N Iam-On, T Boongoen
Human-centric Computing and Information Sciences 7, 1-24, 2017
Comparative study of matrix refinement approaches for ensemble clustering
N Iam-On, T Boongoen
Machine Learning 98, 269-300, 2015
Prediction of student dropout using personal profile and data mining approach
P Meedech, N Iam-On, T Boongoen
Intelligent and Evolutionary Systems: The 19th Asia Pacific Symposium, IES …, 2016
Clustering data with the presence of missing values by ensemble approach
M Pattanodom, N Iam-On, T Boongoen
2016 second asian conference on defence technology (acdt), 151-156, 2016
Diversity-driven generation of link-based cluster ensemble and application to data classification
N Iam-On, T Boongoen
Expert Systems with Applications 42 (21), 8259-8273, 2015
Predicting transitional interval of kidney disease stages 3 to 5 using data mining method
P Panwong, N Iam-On
2016 second Asian conference on defence technology (ACDT), 145-150, 2016
Graph clustering-based discretization of splitting and merging methods (GraphS and GraphM)
K Sriwanna, T Boongoen, N Iam-On
Human-centric Computing and Information Sciences 7 (1), 1-39, 2017
Improving consensus clustering with noise-induced ensemble generation
P Panwong, T Boongoen, N Iam-On
Expert Systems with Applications 146, 113138, 2020
Embedded YARA rules: strengthening YARA rules utilising fuzzy hashing and fuzzy rules for malware analysis
N Naik, P Jenkins, N Savage, L Yang, T Boongoen, N Iam-On, K Naik, ...
Complex & Intelligent Systems 7, 687-702, 2021
Fuzzy-import hashing: A static analysis technique for malware detection
N Naik, P Jenkins, N Savage, L Yang, T Boongoen, N Iam-On
Forensic Science International: Digital Investigation 37, 301139, 2021
Fuzzy-Import Hashing: A malware analysis approach
N Naik, P Jenkins, N Savage, L Yang, T Boongoen, N Iam-On
2020 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE), 1-8, 2020
Clustering data with the presence of attribute noise: a study of noise completely at random and ensemble of multiple k-means clusterings
N Iam-On
International journal of machine learning and cybernetics 11, 491-509, 2020
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