attributenets: an incremental learning method for interpretable     classification

ISCAS OpenIR > 互联网软件技术实验室

	attributenets: an incremental learning method for interpretable classification
	Wu Hu; Wang Yongii; Huai Xiaoyong
	2007
会议名称	11th Pacific-Asia Conference on Knowledge Discovery and Data Mining
会议录名称	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
页码	940-947
会议日期	43973
会议地点	Nanjing, PEOPLES R CHINA
出版地	HEIDELBERGER PLATZ 3, D-14197 BERLIN, GERMANY
出版者	ADVANCES IN KNOWLEDGE DISCOVERY AND DATA MINING, PROCEEDINGS
ISSN	0302-9743
ISBN	978-3-540-71700-3
部门归属	Chinese Acad Sci, Inst Software, Beijing 10080, Peoples R China.
摘要	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
关键词	Data Mining Learning Algorithms Problem Solving Statistical Methods Storage Allocation (Computer)
主办者	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
内容类型	会议论文
URI标识	http://ir.iscas.ac.cn/handle/311060/11076
专题	互联网软件技术实验室
推荐引用方式 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.

条目包含的文件
文件名称/大小	文献类型	版本类型	开放类型	使用许可
an incremental learn（239KB）			开放获取	--	请求全文