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» Evaluating learning algorithms and classifiers
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WWW
2006
ACM
16 years 5 months ago
Large-scale text categorization by batch mode active learning
Large-scale text categorization is an important research topic for Web data mining. One of the challenges in large-scale text categorization is how to reduce the amount of human e...
Steven C. H. Hoi, Rong Jin, Michael R. Lyu
NIPS
2008
15 years 5 months ago
Beyond Novelty Detection: Incongruent Events, when General and Specific Classifiers Disagree
Unexpected stimuli are a challenge to any machine learning algorithm. Here we identify distinct types of unexpected events, focusing on 'incongruent events' when 'g...
Daphna Weinshall, Hynek Hermansky, Alon Zweig, Jie...
ALT
2010
Springer
15 years 6 months ago
Contrast Pattern Mining and Its Application for Building Robust Classifiers
: The ability to distinguish, differentiate and contrast between different data sets is a key objective in data mining. Such ability can assist domain experts to understand their d...
Kotagiri Ramamohanarao
NIPS
2001
15 years 5 months ago
Algorithmic Luckiness
Classical statistical learning theory studies the generalisation performance of machine learning algorithms rather indirectly. One of the main detours is that algorithms are studi...
Ralf Herbrich, Robert C. Williamson
AAAI
2012
13 years 6 months ago
Online Kernel Selection: Algorithms and Evaluations
Kernel methods have been successfully applied to many machine learning problems. Nevertheless, since the performance of kernel methods depends heavily on the type of kernels being...
Tianbao Yang, Mehrdad Mahdavi, Rong Jin, Jinfeng Y...