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Journal Articles
- 2022
[j8]Der-Chiang Li, Ssu-Yang Wang, Kuan-Cheng Huang
, Tung-I Tsai:
Learning class-imbalanced data with region-impurity synthetic minority oversampling technique. Inf. Sci. 607: 1391-1407 (2022)- 2011
- [j7]Gy-Yi Chao, Tung-I Tsai, Te-Jung Lu, Hung-Chang Hsu, Bo-Ying Bao, Wan-Yu Wu, Miao-Ting Lin, Te-Ling Lu:
A new approach to prediction of radiotherapy of bladder cancer cells in small dataset analysis. Expert Syst. Appl. 38(7): 7963-7969 (2011) - 2008
- [j6]Tung-I Tsai, Der-Chiang Li:
Approximate modeling for high order non-linear functions using small sample sets. Expert Syst. Appl. 34(1): 564-569 (2008) - [j5]Tung-I Tsai, Der-Chiang Li:
Utilize bootstrap in small data set learning for pilot run modeling of manufacturing systems. Expert Syst. Appl. 35(3): 1293-1300 (2008) - 2007
- [j4]Der-Chiang Li, Chih-Sen Wu, Tung-I Tsai, Yao-San Lin:
Using mega-trend-diffusion and artificial samples in small data set learning for early flexible manufacturing system scheduling knowledge. Comput. Oper. Res. 34(4): 966-982 (2007) - [j3]Der-Chiang Li, Chun-Wu Yeh, Tung-I Tsai, Yao-Hwei Fang, Susan C. Hu:
Acquiring knowledge with limited experience. Expert Syst. J. Knowl. Eng. 24(3): 162-170 (2007) - [j2]Der-Chiang Li, Hung-Chang Hsu, Tung-I Tsai, Te-Jung Lu, Susan C. Hu:
A new method to help diagnose cancers for small sample size. Expert Syst. Appl. 33(2): 420-424 (2007) - 2006
- [j1]Der-Chiang Li, Chih-Sen Wu, Tung-I Tsai, Fengming M. Chang:
Using mega-fuzzification and data trend estimation in small data set learning for early FMS scheduling knowledge. Comput. Oper. Res. 33: 1857-1869 (2006)
Conference and Workshop Papers
- 2019
- [c2]Tung-I Tsai, Chun-Wu Yeh, Liang-Sian Lin, I-Hsiang Wen:
Improving the Learning Accuracy of the Mega Trend Diffusion Technique for Small Data Sets. IIAI-AAI 2019: 573-578 - 2016
- [c1]Chun-Wu Yeh, Der-Chiang Li, Liang-Sian Lin, Tung-I Tsai:
A Learning Approach with Under-and Over-Sampling for Imbalanced Data Sets. IIAI-AAI 2016: 725-729
Coauthor Index
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