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SAC
2010
ACM
13 years 2 months ago
A study on interestingness measures for associative classifiers
Associative classification is a rule-based approach to classify data relying on association rule mining by discovering associations between a set of features and a class label. Su...
Mojdeh Jalali Heravi, Osmar R. Zaïane
CVPR
2011
IEEE
12 years 12 months ago
Generalized Group Sparse Classifiers with Application in fMRI Brain Decoding
The perplexing effects of noise and high feature dimensionality greatly complicate functional magnetic resonance imaging (fMRI) classification. In this paper, we present a novel f...
Bernard Ng, Rafeef Abugharbieh
ICPR
2006
IEEE
14 years 9 months ago
Learning Policies for Efficiently Identifying Objects of Many Classes
Viola and Jones (VJ) cascade classification methods have proven to be very successful in detecting objects belonging to a single class -- e.g., faces. This paper addresses the mor...
Ahmed M. Elgammal, Ramana Isukapalli, Russell Grei...
ICALT
2005
IEEE
14 years 1 months ago
Phoenix Tool: A Support to Semantic Learning Model
Share and reuse of learning objects are an important issue, that are not solved by simply adding a metadata description. Their contextualisation as well as their level of granular...
Emmanuel Fernandes, Hend Madhour, Sami Miniaoui, M...
COLT
1993
Springer
14 years 8 days ago
Learning from a Population of Hypotheses
We introduce a new formal model in which a learning algorithm must combine a collection of potentially poor but statistically independent hypothesis functions in order to approxima...
Michael J. Kearns, H. Sebastian Seung