A Method of Small Data Set Learning for Early Knowledge Acquisition

TFIR > Department of Marketing Distribution management > journal > Item 987654321/345

Please use this identifier to cite or link to this item: http://163.15.40.127/ir/handle/987654321/345

Title:	A Method of Small Data Set Learning for Early Knowledge Acquisition
Authors:	Chang, Fengming-Michael;邱明源;Chiu, Ming-Yuan;(東方技術學院行銷與流通管理系)
Contributors:	東方技術學院行銷與流通管理系
Keywords:	ANN;FNN;artificial intelligence;early knowledge;machine learning;small data set learning
Date:	2005-02
Issue Date:	2009-11-19 11:22:18 (UTC+8)
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.
Relation:	WSEAS Transactions on Information Science and Applications, Vol.2 no.2, pp.89-94
Appears in Collections:	[Department of Marketing Distribution management] journal

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