attributenets: an incremental learning method for interpretable     classification

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	attributenets: an incremental learning method for interpretable classification
	Wu Hu; Wang Yongii; Huai Xiaoyong
	2007
Conference Name	11th Pacific-Asia Conference on Knowledge Discovery and Data Mining
Source	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Pages	940-947
Conference Date	43973
Conference Place	Nanjing, PEOPLES R CHINA
Publish Place	HEIDELBERGER PLATZ 3, D-14197 BERLIN, GERMANY
Publisher	ADVANCES IN KNOWLEDGE DISCOVERY AND DATA MINING, PROCEEDINGS
ISSN	0302-9743
ISBN	978-3-540-71700-3
Department	Chinese Acad Sci, Inst Software, Beijing 10080, Peoples R China.
English Abstract	Incremental learning is of more and more importance in real world data mining scenarios. Memory cost and adaptation cost are two major concerns of incremental learning algorithms. In this paper we provide a novel incremental learning method, A
Keyword	Data Mining Learning Algorithms Problem Solving Statistical Methods Storage Allocation (Computer)
Sponsorship	Nanjing Univ, LAMDA Grp, Nanjing Univ, Aeronaut & Astronaut, Japanese Soc Artificial Intelligence, Singapore Inst Stat, Natl Nat Sci Fdn China, Microsoft adCenter Labs, NEC Labs, China, Microsoft Res Asia, Salford Syst, KC Wong Educ Fdn
Content Type	会议论文
URI	http://ir.iscas.ac.cn/handle/311060/11076
Collection	互联网软件技术实验室
Recommended Citation GB/T 7714	Wu Hu,Wang Yongii,Huai Xiaoyong. attributenets: an incremental learning method for interpretable classification[C]. HEIDELBERGER PLATZ 3, D-14197 BERLIN, GERMANY:ADVANCES IN KNOWLEDGE DISCOVERY AND DATA MINING, PROCEEDINGS,2007:940-947.

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