A method of small data set learning for early knowledge acquisition

  • Authors:

  • Fengming Michael Chang;Ming-Yuan Chiu

  • Affiliations:

  • Department of Industrial Engineering and Management, Tungfang Institute of Technology, Hu-Nei Shang, Kaohsiung Hsien, Taiwan;Department of Industrial Engineering and Management, Tungfang Institute of Technology, Hu-Nei Shang, Kaohsiung Hsien, Taiwan

  • Venue:
  • AIKED'05 Proceedings of the 4th WSEAS International Conference on Artificial Intelligence, Knowledge Engineering Data Bases
  • Year:
  • 2005

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Abstract

Many machine learning approaches in the field of Artificial Intelligence (AI) have been developed. Most of them rely on using large data sets to build up knowledge. However, a system usually has only few data in the early stages for use. Consequently, Early Knowledge acquisition becomes a challenging problem, and this problem is unfortunately getting more urgent while the life cycle of a product is getting shorter in today's environment. This article presents a method to increase the accuracy of learning using small data.