Non-parametric statistical assistance in virtual sample selection for small data set prediction

Yao San Lin, Liang Sian Lin, Der-Chiang Li, Wei Lin Liao

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Science learned models based on limited data are usually fragile, researchers suggest the adoption of virtual samples to improve the prediction model. In this study, nonparametric statistical tool, Kolmogorov-Smirnov test, is introduced to examine the distribution of virtual samples without any assumption about the underlying population. The examination procedure would help control the quality of the generated virtual samples, such that the prediction model can be more robust with the basis of high quality virtual samples. Experimental results show that the prediction model with statistical test procedure performs better than the original one, with more stable and improved accuracies, and the examination procedure can effectively lower the prediction error.

Original languageEnglish
Title of host publicationProceedings - 3rd International Conference on Applied Computing and Information Technology and 2nd International Conference on Computational Science and Intelligence, ACIT-CSI 2015
EditorsKensei Tsuchida, Naohiro Ishii, Takaaki Goto, Satoshi Takahashi
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages369-373
Number of pages5
ISBN (Electronic)9781467396424
DOIs
Publication statusPublished - 2015 Nov 23
Event3rd International Conference on Applied Computing and Information Technology and 2nd International Conference on Computational Science and Intelligence, ACIT-CSI 2015 - Okayama, Japan
Duration: 2015 Jul 122015 Jul 16

Publication series

NameProceedings - 3rd International Conference on Applied Computing and Information Technology and 2nd International Conference on Computational Science and Intelligence, ACIT-CSI 2015

Other

Other3rd International Conference on Applied Computing and Information Technology and 2nd International Conference on Computational Science and Intelligence, ACIT-CSI 2015
CountryJapan
CityOkayama
Period15-07-1215-07-16

All Science Journal Classification (ASJC) codes

  • Artificial Intelligence
  • Computer Networks and Communications
  • Computer Science Applications
  • Human-Computer Interaction
  • Information Systems

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  • Cite this

    Lin, Y. S., Lin, L. S., Li, D-C., & Liao, W. L. (2015). Non-parametric statistical assistance in virtual sample selection for small data set prediction. In K. Tsuchida, N. Ishii, T. Goto, & S. Takahashi (Eds.), Proceedings - 3rd International Conference on Applied Computing and Information Technology and 2nd International Conference on Computational Science and Intelligence, ACIT-CSI 2015 (pp. 369-373). [7336090] (Proceedings - 3rd International Conference on Applied Computing and Information Technology and 2nd International Conference on Computational Science and Intelligence, ACIT-CSI 2015). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ACIT-CSI.2015.70