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ORCIDKrung Sinapiromsaran
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2020 – today
- 2024
[c14]Zehong Fan, Arthorn Luangsodsai, Krung Sinapiromsaran:
Mass-Ratio-Average-Absolute-Deviation Based Outlier Factor for Anomaly Scoring. JCSSE 2024: 488-493- 2023
- [c13]Worawit Jitpakdeebodin
, Krung Sinapiromsaran:
Random forest algorithm using quartile-pattern bootstrapping for a class imbalanced problem. IVSP 2023: 191-196 - [c12]Alon Basin, Arthorn Luangsodsai, Krung Sinapiromsaran:
Static Class-Level Approach For Test Impact Analysis. JCSSE 2023: 321-326 - 2021
- [c11]Piboon Polvimoltham, Krung Sinapiromsaran:
Mass Ratio Variance Majority Undersampling and Minority Oversampling Technique for Class Imbalance. FSDM 2021: 152-161 - [c10]Phichapop Changsakul, Somjai Boonsiri, Krung Sinapiromsaran:
Mass-ratio-variance based Outlier Factor. JCSSE 2021: 1-5
2010 – 2019
- 2017
- [j5]Chumphol Bunkhumpornpat, Krung Sinapiromsaran:
DBMUTE: density-based majority under-sampling technique. Knowl. Inf. Syst. 50(3): 827-850 (2017) - [j4]Kesinee Boonchuay, Krung Sinapiromsaran, Chidchanok Lursinsap:
Decision tree induction based on minority entropy for the class imbalance problem. Pattern Anal. Appl. 20(3): 769-782 (2017) - [c9]Paisit Khanarsa, Krung Sinapiromsaran:
Multiple ARIMA subsequences aggregate time series model to forecast cash in ATM. KST 2017: 83-88 - 2015
- [j3]Chumphol Bunkhumpornpat, Krung Sinapiromsaran:
CORE: core-based synthetic minority over-sampling and borderline majority under-sampling technique. Int. J. Data Min. Bioinform. 12(1): 44-58 (2015) - [c8]Suebkul Kanchanasuk, Krung Sinapiromsaran:
Proceedings in Adaptation, Learning and Optimization. IES 2015: 99-107 - [c7]Panote Songwattanasiri, Krung Sinapiromsaran:
Proceedings in Adaptation, Learning and Optimization. IES 2015: 109-117 - 2014
- [j2]Aua-aree Boonperm, Krung Sinapiromsaran:
Artificial-free simplex algorithm based on the non-acute constraint relaxation. Appl. Math. Comput. 234: 385-401 (2014) - 2012
- [j1]Chumphol Bunkhumpornpat, Krung Sinapiromsaran, Chidchanok Lursinsap:
DBSMOTE: Density-Based Synthetic Minority Over-sampling TEchnique. Appl. Intell. 36(3): 664-684 (2012) - [c6]Krung Sinapiromsaran, Narudom Techaval:
Network intrusion detection using multi-attributed frame decision tree. DICTAP 2012: 203-207 - 2011
- [c5]Chumphol Bunkhumpornpat, Krung Sinapiromsaran, Chidchanok Lursinsap:
MUTE: Majority under-sampling technique. ICICS 2011: 1-4 - [c4]Kesinee Boonchuay, Krung Sinapiromsaran, Chidchanok Lursinsap:
Minority split and gain ratio for a class imbalance. FSKD 2011: 2060-2064 - 2010
- [c3]Wacharasak Siriseriwan, Krung Sinapiromsaran:
Attributes Scaling for K-means Algorithm Controlled by Misclassification of All Clusters. WKDD 2010: 220-223
2000 – 2009
- 2009
- [c2]Chumphol Bunkhumpornpat, Krung Sinapiromsaran, Chidchanok Lursinsap:
Safe-Level-SMOTE: Safe-Level-Synthetic Minority Over-Sampling TEchnique for Handling the Class Imbalanced Problem. PAKDD 2009: 475-482 - 2000
- [c1]Michael C. Ferris, Todd S. Munson, Krung Sinapiromsaran:
A practical approach to sample-path simulation optimization. WSC 2000: 795-804
Coauthor Index
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