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ICMCS
2006
IEEE
151views Multimedia» more  ICMCS 2006»
14 years 1 months ago
Support Vector Machine for Multiple Feature Classifcation
In this paper an effective method of using SVM classifier for multiple feature classification is proposed. Compared with traditional combination methods where all needed base clas...
Bing-Yu Sun, Moon-Chuen Lee
TKDE
2008
134views more  TKDE 2008»
13 years 7 months ago
Sensor-Based Abnormal Human-Activity Detection
With the availability of affordable sensors and sensor networks, sensor-based human-activity recognition has attracted much attention in artificial intelligence and ubiquitous comp...
Jie Yin, Qiang Yang, Jeffrey Junfeng Pan
ICML
1999
IEEE
14 years 8 months ago
Lazy Bayesian Rules: A Lazy Semi-Naive Bayesian Learning Technique Competitive to Boosting Decision Trees
Lbr is a lazy semi-naive Bayesian classi er learning technique, designed to alleviate the attribute interdependence problem of naive Bayesian classi cation. To classify a test exa...
Zijian Zheng, Geoffrey I. Webb, Kai Ming Ting
KDD
2006
ACM
129views Data Mining» more  KDD 2006»
14 years 8 months ago
Suppressing model overfitting in mining concept-drifting data streams
Mining data streams of changing class distributions is important for real-time business decision support. The stream classifier must evolve to reflect the current class distributi...
Haixun Wang, Jian Yin, Jian Pei, Philip S. Yu, Jef...
EOR
2007
101views more  EOR 2007»
13 years 7 months ago
Comprehensible credit scoring models using rule extraction from support vector machines
In recent years, Support Vector Machines (SVMs) were successfully applied to a wide range of applications. Their good performance is achieved by an implicit non-linear transformat...
David Martens, Bart Baesens, Tony Van Gestel, Jan ...