 | 2011 |
|---|
| 9 |       | Chang-Hwan Lee,
Fernando Gutierrez,
Dejing Dou:
Calculating Feature Weights in Naive Bayes with Kullback-Leibler Measure.
ICDM 2011: 1146-1151 |
| 8 |  | Chang-Hwan Lee:
Combining Different Classifiers with Identical Features in Co-Training Method.
MLDM Posters 2011: 49-58 |
| 2007 |
|---|
| 7 | | Chang-Hwan Lee:
IMSP: An information theoretic approach for multi-dimensional sequential pattern mining.
Appl. Intell. 26(3): 231-242 (2007) |
| 6 | | Chang-Hwan Lee:
Improving classification performance using unlabeled data: Naive Bayesian case.
Knowl.-Based Syst. 20(3): 220-224 (2007) |
| 5 | | Chang-Hwan Lee:
A Hellinger-based discretization method for numeric attributes in classification learning.
Knowl.-Based Syst. 20(4): 419-425 (2007) |
| 2006 |
|---|
| 4 | | Chang-Hwan Lee:
A Semi-naive Bayesian Learning Method for Utilizing Unlabeled Data.
KES (1) 2006: 187-194 |
| 2005 |
|---|
| 3 | | Chang-Hwan Lee:
Inducing Sequential Patterns from Multidimensional Time Series Data.
Australian Conference on Artificial Intelligence 2005: 900-903 |
| 2 | | Chang-Hwan Lee:
Discretizing Continuous Attributes Using Information Theory.
ISCIS 2005: 493-502 |
| 1 | | Chang-Hwan Lee:
An Entropy-Based Approach for Generating Multi-dimensional Sequential Patterns.
PKDD 2005: 585-592 |
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