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» A Theoretical Framework for Dynamic Classifier Selection
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DIS
2008
Springer
13 years 6 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
12 years 12 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 2 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 4 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»
13 years 11 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...