Generating multi-modality virtual samples with soft DBSCAN for small data set learning

Liang Sian Lin, Der-Chiang Li, Wei Hao Yu, Yu Mei Hsueh

研究成果: Conference contribution

摘要

Owing to the factors of cost and time limit, the number of samples is usually small in the early stages of manufacturing systems. When the number of available data is small, traditional statistic techniques have difficulty to obtain robust analyses. Therefore, based on a uni-modality distribution assumption, many researchers have proposed virtual sample generation methods to expand the training sample size to enhance the performance of small data set learning. In practice, small data may be following a multi-modality distribution. Therefore, in order to solve multi-modal small data sets, this study proposes a new approach to create multi-modality Weibull virtual samples, where we use the maximal p-value to estimate parameters of the Weibull distribution. In addition, the soft DBSCAN method is used to identify a suitable number of modalities. One data set is employed to check the performance of the proposed method, and comparisons are made by the prediction on root mean square error. The results using a paired t-test show that the proposed method has a superior prediction performance than that of the mega-trend-diffusion method using a uni-modality triangular membership function.

原文English
主出版物標題Proceedings - 3rd International Conference on Applied Computing and Information Technology and 2nd International Conference on Computational Science and Intelligence, ACIT-CSI 2015
編輯Kensei Tsuchida, Naohiro Ishii, Takaaki Goto, Satoshi Takahashi
發行者Institute of Electrical and Electronics Engineers Inc.
頁面363-368
頁數6
ISBN(電子)9781467396424
DOIs
出版狀態Published - 2015 十一月 23
事件3rd International Conference on Applied Computing and Information Technology and 2nd International Conference on Computational Science and Intelligence, ACIT-CSI 2015 - Okayama, Japan
持續時間: 2015 七月 122015 七月 16

出版系列

名字Proceedings - 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
國家/地區Japan
城市Okayama
期間15-07-1215-07-16

All Science Journal Classification (ASJC) codes

  • 人工智慧
  • 電腦網路與通信
  • 電腦科學應用
  • 人機介面
  • 資訊系統

指紋

深入研究「Generating multi-modality virtual samples with soft DBSCAN for small data set learning」主題。共同形成了獨特的指紋。

引用此