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GECCO
2009
Springer
188views Optimization» more  GECCO 2009»
14 years 17 days ago
Exploiting multiple classifier types with active learning
Many approaches to active learning involve training one classifier by periodically choosing new data points about which the classifier has the least confidence, but designing a co...
Zhenyu Lu, Josh Bongard
RSFDGRC
2007
Springer
236views Data Mining» more  RSFDGRC 2007»
14 years 2 months ago
Constructing Associative Classifier Using Rough Sets and Evidence Theory
Constructing accurate classifier based on association rule is an important and challenging task in data mining. In this paper, a novel combination strategy based on rough sets (RST...
Yuan-Chun Jiang, Ye-Zheng Liu, Xiao Liu, Jie-Kui Z...
KDD
2005
ACM
161views Data Mining» more  KDD 2005»
14 years 9 months ago
Combining email models for false positive reduction
Machine learning and data mining can be effectively used to model, classify and discover interesting information for a wide variety of data including email. The Email Mining Toolk...
Shlomo Hershkop, Salvatore J. Stolfo
ERCIMDL
2006
Springer
204views Education» more  ERCIMDL 2006»
14 years 11 days ago
Comparing and Combining Two Approaches to Automated Subject Classification of Text
A machine-learning and a string-matching approach to automated subject classification of text were compared, as to their performance, advantages and downsides. The former approach ...
Koraljka Golub, Anders Ardö, Dunja Mladenic, ...
AVBPA
2001
Springer
128views Biometrics» more  AVBPA 2001»
14 years 10 days ago
Fingerprint Classification with Combinations of Support Vector Machines
Abstract. We report about some experiments on the fingerprint database NIST-4 using different combinations of Support Vector Machine (SVM) classifiers. Images have been preprocesse...
Yuan Yao, Paolo Frasconi, Massimiliano Pontil