Improving knowledge acquisition capability of M5' model tree on small datasets

Chun Hao Tsai, Der Chiang Li

研究成果: Conference contribution

2 引文 斯高帕斯(Scopus)

摘要

In many small dataset learning tasks, however, owing to the incomplete data structure, the explicit information for decision making is limited. This research aims to learn more information hidden inside the incomplete data by adding more samples to strengthen data structures. Based on the prior knowledge provided by the M5' model tree, the proposed research mechanism generates artificial samples to enhance the crisp data structures. Besides, the ability to handle nominal attributes is also provided in this research, while it is usually lacking in most sample generation approaches. In the experiments, the results show that the knowledge acquisition capability and the predictive accuracies of M5' are improved.

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379-386
頁數8
ISBN(電子)9781467396424
DOIs
出版狀態Published - 2015 11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 7月 122015 7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

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