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» A Theoretical Framework for Dynamic Classifier Selection
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DIS
2008
Springer
13 years 10 months ago
Unsupervised Classifier Selection Based on Two-Sample Test
We propose a well-founded method of ranking a pool of m trained classifiers by their suitability for the current input of n instances. It can be used when dynamically selecting a s...
Timo Aho, Tapio Elomaa, Jussi Kujala
ACCV
2010
Springer
13 years 3 months ago
Efficient Visual Object Tracking with Online Nearest Neighbor Classifier
Abstract. A tracking-by-detection framework is proposed that combines nearest-neighbor classification of bags of features, efficient subwindow search, and a novel feature selection...
Steve Gu, Ying Zheng, Carlo Tomasi
ACL
2009
13 years 6 months ago
A Framework of Feature Selection Methods for Text Categorization
In text categorization, feature selection (FS) is a strategy that aims at making text classifiers more efficient and accurate. However, when dealing with a new task, it is still d...
Shoushan Li, Rui Xia, Chengqing Zong, Chu-Ren Huan...
TNN
2008
124views more  TNN 2008»
13 years 8 months ago
Just-in-Time Adaptive Classifiers - Part II: Designing the Classifier
Aging effects, environmental changes, thermal drifts, and soft and hard faults affect physical systems by changing their nature and behavior over time. To cope with a process evolu...
Cesare Alippi, Manuel Roveri
SMC
2007
IEEE
156views Control Systems» more  SMC 2007»
14 years 2 months ago
Dynamic fusion of classifiers for fault diagnosis
—This paper considers the problem of temporally fusing classifier outputs to improve the overall diagnostic classification accuracy in safety-critical systems. Here, we discuss d...
Satnam Singh, Kihoon Choi, Anuradha Kodali, Krishn...