Chang-Hwan Lee

23 papers A* 1C 3Journal 10Unranked 9
YearRankTypeTitle / Venue / Authors
2023 J jnl
The Effect of Defection in Maximizing Group Benefit.
Appl. Artif. Intell.
Chanseung Lee, Chang-Hwan Lee
2018 J jnl
An information-theoretic filter approach for value weighted classification learning in naive Bayes.
Data Knowl. Eng.
Chang-Hwan Lee
2018 J jnl
Multi-label classification of documents using fine-grained weights and modified co-training.
Intell. Data Anal.
Chang-Hwan Lee
2016 — conf
Assigning Different Weights to Feature Values in Naive Bayes.
SCDS
Chang-Hwan Lee
2016 — conf
Calculating different weights in feature values in logistic regression.
ICCIP
Chang-Hwan Lee
2015 J jnl
A gradient approach for value weighted classification learning in naive Bayes.
Knowl. Based Syst.
Chang-Hwan Lee
2015 J jnl
A multi-phase approach for classifying multi-dimensional sequence data.
Intell. Data Anal.
Chang-Hwan Lee
2015 C ed.
Current Approaches in Applied Artificial Intelligence - 28th International Conference on Industrial, Engineering and Other Applications of Applied Intelligent Systems, IEA/AIE 2015, Seoul, South Korea, June 10-12, 2015, Proceedings
IEA/AIE
Moonis Ali, Young Sig Kwon, Chang-Hwan Lee, Juntae Kim, Yongdai Kim
2015 C conf
Improving Document Classification Using Fine-Grained Weights.
IEA/AIE
Soohwan Song, Chang-Hwan Lee
2014 J jnl
A Hellinger-Based Importance Measure of Association Rules for Classification Learning.
Int. J. Intell. Syst.
Chang-Hwan Lee
2014 — conf
A New Fine-Grained Weighting Method in Multi-Label Text Classification.
MAICS
Chang-Hwan Lee
2014 J jnl
An Information-Theoretic filter Method for Feature Weighting in Naive Bayes.
Int. J. Pattern Recognit. Artif. Intell.
Chang-Hwan Lee
2013 — conf
QoS-aware hierarchical token bucket (QHTB) queuing disciplines for QoS-guaranteed Diffserv provisioning with optimized bandwidth utilization and priority-based preemption.
ICOIN
Chang-Hwan Lee, Young-Tak Kim
2012 C conf
Performance analysis of multi-layered protection switching with control-forwarding separation.
APNOMS
Kwangtae Jeong, Chang-Hwan Lee, Young-Tak Kim
2011 A* conf
Calculating Feature Weights in Naive Bayes with Kullback-Leibler Measure.
ICDM
Chang-Hwan Lee, Fernando Gutierrez, Dejing Dou
2011 — conf
Combining Different Classifiers with Identical Features in Co-Training Method.
MLDM Posters
Chang-Hwan Lee
2007 J jnl
A Hellinger-based discretization method for numeric attributes in classification learning.
Knowl. Based Syst.
Chang-Hwan Lee
2007 J jnl
IMSP: An information theoretic approach for multi-dimensional sequential pattern mining.
Appl. Intell.
Chang-Hwan Lee
2007 J jnl
Improving classification performance using unlabeled data: Naive Bayesian case.
Knowl. Based Syst.
Chang-Hwan Lee
2006 — conf
A Semi-naive Bayesian Learning Method for Utilizing Unlabeled Data.
KES (1)
Chang-Hwan Lee
2005 — conf
An Entropy-Based Approach for Generating Multi-dimensional Sequential Patterns.
PKDD
Chang-Hwan Lee
2005 — conf
Discretizing Continuous Attributes Using Information Theory.
ISCIS
Chang-Hwan Lee
2005 — conf
Inducing Sequential Patterns from Multidimensional Time Series Data.
Australian Conference on Artificial Intelligence
Chang-Hwan Lee