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2010 – 2019
- 2015
[j3]Xiaojun Ren, Hyontai Sug, HoonJae Lee:
A New Estimation Model for Wireless Sensor Networks Based on the Spatial-Temporal Correlation Analysis. J. Inform. and Commun. Convergence Engineering 13(2) (2015)- 2013
- [c24]Hyontai Sug:
Better Induction Models for Classification of Forest Cover. MUSIC 2013: 185-189 - 2012
- [j2]Hyontai Sug:
Applying Randomness Effectively Based on Random Forests for Classification Task of Datasets of Insufficient Information. J. Appl. Math. 2012: 258054:1-258054:13 (2012) - [c23]Hyontai Sug:
Better Decision Tree Induction for Limited Data Sets of Liver Disease. FGIT-MulGraB/BSBT/IUrC 2012: 88-93 - 2011
- [c22]Hyontai Sug:
Using Quick Decision Tree Algorithm to Find Better RBF Networks. ACIIDS (1) 2011: 207-217 - [c21]Hyontai Sug:
The Effect of Biased Sampling in Radial Basis Function Networks for Data Mining. FGIT-MulGraB (1) 2011: 299-306 - [c20]Hyontai Sug:
An Effective Method to Find Better Data Mining Model Using Inferior Class Oversampling. ICHIT (2) 2011: 576-583
2000 – 2009
- 2009
- [c19]Hyontai Sug:
A Structural Sampling Technique for Better Decision Trees. ACIIDS 2009: 24-27 - [c18]Hyontai Sug:
Sampling scheme for better RBF network. ICHIT 2009: 413-416 - [c17]Hyontai Sug:
An empirical improvement of the accuracy of RBF networks. ICIS 2009: 708-712 - 2008
- [j1]Hyontai Sug:
A Rule Set Generation Technique for Better Decision Making. J. Digit. Content Technol. its Appl. 2(2): 60-63 (2008) - [c16]Hyontai Sug:
Finding Hidden Functional Dependencies in Relations Efficiently. Artificial Intelligence and Pattern Recognition 2008: 228-231 - [c15]Hyontai Sug:
Finding Association Rules in Large Relations for Possible Normalization. IKE 2008: 165-169 - [c14]Hyontai Sug:
Applying Rough Sets to Maintain Data Consistency for High Degree Relations. NCM (2) 2008: 244-247 - 2007
- [c13]Hyontai Sug:
Finding More Interesting Rules with Decision Trees fo Very Large Databases. IC-AI 2007: 476-480 - [c12]Hyontai Sug:
Discovering Rules about Customer Behavior for Logistics using RFID Tags. IKE 2007: 86-89 - 2006
- [c11]Hyontai Sug:
Class Selection Avoiding Key-like Property for Better Precise Rules. DMIN 2006: 372-375 - [c10]Hyontai Sug:
Generating Decision Trees with Boughs. IC-AI 2006: 545-550 - [c9]Hyontai Sug:
Using Reliable Short Rules to Avoid Unnecessary Tests in Decision Trees. MICAI 2006: 604-611 - 2005
- [c8]Hyontai Sug:
A Comprehensively Sized Decision Tree Generation Method for Interactive Data Mining of Very Large Databases. ADMA 2005: 141-148 - [c7]Hyontai Sug:
Applying Rapid Knowledge Model in Finding Categorical. IC-AI 2005: 327-332 - 2004
- [c6]Hyontai Sug:
Determining a Good Decision Attribute for Knowledge Discovery in Databases. IC-AI 2004: 288-294 - [c5]Hyontai Sug:
Reducing on the Number of Testing Items in the Branches of Decision Trees. ICCSA (4) 2004: 158-166 - [c4]Hyontai Sug:
A Discovery of Rules of Hierarch for Very Large Databases. IKE 2004: 353-357 - 2003
- [c3]Hyontai Sug:
An Empirical Study on Possibility of Improvement on Decision Trees for Large Databases. IASSE 2003: 89-92 - [c2]Hyontai Sug:
Comparison of Multidimensional Association Rules with Decision Trees for Large Database. IC-AI 2003: 121-126 - [c1]Hyontai Sug:
Generating Smaller Decision Trees for Understandability Using Frequent Attributes. IKE 2003: 142-148
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