| Rough set model based feature selection for mixed-type data with feature space decomposition KJ Kim, CH Jun Expert Systems with Applications 103, 196-205, 2018 | 24 | 2018 |
| Variable selection under missing values and unlabeled data in semiconductor processes KJ Kim, KJ Kim, CH Jun, IG Chong, GY Song IEEE Transactions on Semiconductor Manufacturing 32 (1), 121-128, 2018 | 13 | 2018 |
| Designing of an attribute control chart for two-stage process M Aslam, M Azam, KJ Kim, CH Jun Measurement and Control 51 (7-8), 285-292, 2018 | 8 | 2018 |
| A statistical procedure of analyzing container ship operation data for finding fuel consumption patterns KJ Kim, SD Lee, CH Jun, KM Park, SS Byeon The Korean Journal of Applied Statistics 30 (5), 633-645, 2017 | 8 | 2017 |
| A mixed control chart adapted to the truncated life test based on the Weibull distribution N Khan, M Aslam, KJ Kim, CH Jun Operations Research and Decisions 27 (1), 43-55, 2017 | 7 | 2017 |
| Dynamic mutual information-based feature selection for multi-label learning KJ Kim, CH Jun Intelligent Data Analysis, 1-19, 2023 | 2 | 2023 |
| How to Pick the Best Source Data? Measuring Transferability for Heterogeneous Domains S Park, H Xu, T Kim, I Hwang, KJ Kim, U Kang arXiv preprint arXiv:1912.13366, 2019 | | 2019 |
| Feature selection based on rough set theory using feature space decomposition for mixed-type data KJ Kim, CH Jun 한국경영과학회 학술대회논문집, 5014-5020, 2016 | | 2016 |
| Feature Selection Based on Rough Set Theory Using Feature Space Decomposition for Mixed-type Data Classification KJ Kim, CH Jun | | |
