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AUSDM
2008
Springer
211views Data Mining» more  AUSDM 2008»
13 years 11 months ago
LBR-Meta: An Efficient Algorithm for Lazy Bayesian Rules
LBR is a highly accurate classification algorithm, which lazily constructs a single Bayesian rule for each test instance at classification time. However, its computational complex...
Zhipeng Xie
VTS
2007
IEEE
203views Hardware» more  VTS 2007»
14 years 3 months ago
Multiple Bit Upset Tolerant Memory Using a Selective Cycle Avoidance Based SEC-DED-DAEC Code
Conventional error correcting code (ECC) schemes used in memories and caches cannot correct double bit errors caused by a single event upset (SEU). As memory density increases, mu...
Avijit Dutta, Nur A. Touba
AUSAI
2004
Springer
14 years 1 months ago
Using Classification to Evaluate the Output of Confidence-Based Association Rule Mining
Abstract. Association rule mining is a data mining technique that reveals interesting relationships in a database. Existing approaches employ different parameters to search for int...
Stefan Mutter, Mark Hall, Eibe Frank
ICDM
2006
IEEE
154views Data Mining» more  ICDM 2006»
14 years 3 months ago
Mining and Predicting Duplication over Peer-to-Peer Query Streams
Many previous works of data mining user queries in Peer-to-Peer systems focused their attention on the distribution of query contents. However, few has been done towards a better ...
Shicong Meng, Yifeng Shao, Cong Shi, Dingyi Han, Y...
TNN
2008
182views more  TNN 2008»
13 years 9 months ago
Large-Scale Maximum Margin Discriminant Analysis Using Core Vector Machines
Abstract--Large-margin methods, such as support vector machines (SVMs), have been very successful in classification problems. Recently, maximum margin discriminant analysis (MMDA) ...
Ivor Wai-Hung Tsang, András Kocsor, James T...